Jan Steemann had a talk at Javascript Everywhere in Paris 2012 on Javascript in Arangodb an open source NoSQL database. With ArangoDB you can use Javascript and/or Ruby (mruby) as embedded language
This document discusses using JavaScript in databases. It describes how JavaScript can be used in the database for transactions defined as functions, graph traversal, and having no backend code, just an API. It provides examples of using JavaScript for transactions and graph traversal in ArangoDB.
The document outlines an agenda for a workshop on ArangoDB and Ashikawa. The agenda includes introducing ArangoDB, installing it, performing CRUD operations, using the query language, and building a small example with the Ruby driver Ashikawa. It also provides information on importing data and performing queries on ArangoDB.
The document discusses using the MRuby scripting language in databases. It provides an overview of NoSQL databases and the ArangoDB multi-model database. It then discusses use cases for scripting languages in databases for tasks like enriching results and computing values. The document compares MRuby and V8, noting MRuby is simpler to embed but slower. It argues MRuby may be an alternative embedding if performance is not critical or can be improved with LLVM compilation to machine code.
In this hotcode 2013 talk Lucas and Frank gave an overview over NoSQL and explained why it is a good idea to use Javascript also in the database environment.
Max Neunhöffer presents on the future of NoSQL databases and argues multi-model databases will become the standard. He discusses different NoSQL data models like document stores, key-value stores, graph databases and column-oriented databases. He advocates the benefits of a polyglot persistence approach but notes the disadvantages of managing multiple databases. Max introduces ArangoDB as a multi-model database that supports documents, graphs and key-value in a single database to provide the benefits of polyglot persistence without the disadvantages. He provides examples of how ArangoDB has been used and outlines its features including queries, extensibility and horizontal scalability. Max predicts that in five years, the default approach will be to use a
Introduction to ArangoDB (nosql matters Barcelona 2012)ArangoDB Database
- The document discusses ArangoDB, an open source multi-model database that supports documents, graphs, and key-value stores.
- It began development in 2011 and reached version 1.0 in 2012. The database aims to provide a universal solution as requirements change and scale.
- ArangoDB offers high performance, a query language, extensions via actions, and supports features like replication and sharding.
ArangoDB is a native multi-model database system developed by triAGENS GmbH. The database system supports three important data models (key/value, documents, graphs) with one database core and a unified query language AQL (ArangoDB Query Language). ArangoDB is a NoSQL database system but AQL is similar in many ways to SQL
The document discusses query mechanisms for NoSQL databases. It begins by describing how relational databases require normalization of data into tables and use SQL for queries. NoSQL databases are introduced as being non-relational, schema-free, and having simple APIs. Document stores are highlighted as a type of NoSQL database that can natively store hierarchical data without normalization. Specific document stores like CouchDB and MongoDB are described, showing how data can be stored and queried in documents through HTTP requests or a mongo client. Map-reduce functions are also discussed as a way to perform complex queries across collections of documents.
A Graph Database That Scales - ArangoDB 3.7 Release WebinarArangoDB Database
örg Schad (Head of Engineering and ML) and Chris Woodward (Developer Relations Engineer) introduce the new capabilities to work with graph in a distributed setting. In addition explain and showcase the new fuzzy search within ArangoDB's search engine as well as JSON schema validation.
Get started with ArangoDB: https://www.arangodb.com/arangodb-tra...
Explore ArangoDB Cloud for free with 1-click demos: https://cloud.arangodb.com/home
ArangoDB is a native multi-model database written in C++ supporting graph, document and key/value needs with one engine and one query language. Fulltext search and ranking is supported via ArangoSearch the fully integrated C++ based search engine in ArangoDB.
OrientDB: Unlock the Value of Document Data RelationshipsFabrizio Fortino
a) A general introduction of graph databases and OrientDB,
b) Why connected data has more value than just data,
c)How to "have fun" with OrientDB combining documents with graphs via SQL,
d) A use case on how OrientDB has helped to raise standards in Irish Public Office.
On OrientDB: NOSQL document databases provide an elegant way to deal with data in different shapes enabling developers to create better and faster products quickly. The main goal of these systems is to find the most efficient solution to manage data itself. With the Big Data Explosion we need to deal with a myriad of highly interconnected information. The challenge now is not only on how to store data but on how to manage, analyse, traverse and use your data within the context of relationships. Graph databases shine at maintaining highly connected data and is the fastest growing category in database management systems: 2014 registered an increase of 250% in terms of adoption and Forrester Research predicts that more than a quarter of enterprises will be using graphs by 2017. OrientDB combines more than one NOSQL model offering the unique flexibility of modelling data in the form of either documents, or graphs, while incorporating object oriented programming as a way of encapsulating relationships.
The document discusses OrientDB, a document-graph database. It provides an overview of key OrientDB concepts like documents, vertices, edges, classes, clusters, and properties. It also compares the relational and graph data models. The presentation was given by Greg McCarvell and introduces Node.js integration with OrientDB through examples.
This document discusses connecting an iOS app to a REST API. It covers using a networking library like AFNetworking to make requests, parsing JSON responses, storing data locally using Core Data, and libraries like RestKit that integrate these steps by mapping JSON to Core Data entities and handling background threading. Authentication using OAuth is also briefly mentioned.
Skype uses PostgreSQL for over 100 database servers and 200 databases to support its online services. It partitions data across multiple databases for scalability and uses tools like pgBouncer, PL/Proxy, SkyTools, PgQ, and Londiste to connect, load balance, and replicate data between databases. This complex database architecture has allowed Skype to grow significantly while remaining easy to manage.
Solid pods and the future of the spatial webKurt Cagle
This document discusses Solid Pods and their potential role in the future of the spatial web. Solid Pods are small, deployable graph databases that follow the principles of the Solid project, including allowing individuals to own and have granular control over their data. Solid Pods address issues that limited the adoption of earlier semantic web efforts. They could store scene graphs, serve as data catalogs, support distributed ledgers, and more. As graph databases, Pods are well-suited to power spatial applications through capabilities like hosting knowledge graphs and serving as intermediate calculation nodes. Standards bodies are exploring how Spatial Web specifications could adopt and extend the Solid Pod architecture.
This is a comprehensive slide on implementing web service in iOS . There are basic information on Web Service . There are steps of using web service in iOS. The presentation emphasized on XML Parsing .
The document discusses fetching and parsing web content in iOS applications. It covers using NSURLConnection to fetch HTTP content, parsing XML with NSXMLParser and third party libraries, and parsing JSON with NSJSONSerialization. Options for XML parsing include SAX and DOM approaches, and common third party XML parsing libraries are mentioned. Examples of fetching weather data from a web service in JSON format are also provided.
Mubashar Iqbal presented on PostgreSQL, an open-source object-relational database system. PostgreSQL prioritizes reliability, security, and standards compliance. It supports Linux, Unix, Windows and is programmed through interfaces like C/C++, Java, .NET, PHP and Python. Common uses include ERP, data warehousing, and network tools. Prominent users include Yahoo, Sony, Reddit, and Skype. Key features include ACID compliance, online backup, point-in-time recovery, and SSL encryption.
Column-oriented databases store data by column rather than by row. This allows fast retrieval of entire columns of data with one read operation. Column-oriented databases are well-suited for analytical queries that retrieve many rows but only a few columns, as only the needed columns are read from disk. Row-oriented databases are better for transactional queries that retrieve or update individual rows. The type of data storage - row-oriented or column-oriented - depends on the types of queries that will be run against the data.
Tutorial on RDFa, to be held at ISWC2010 in Shanghai, China. (I was supposed to hold the tutorial but last minute issues made it impossible for me to travel there...)
ODTUG Webcast - Thinking Clearly about XMLMarco Gralike
Presentation slides used during ODTUG Webcast on the 19th of January explaining first steps in Oracle XMLDB (including extended demo's)
https://www3.gotomeeting.com/register/660686966
This document discusses OrientDB, an open source NoSQL document database. It provides high performance and scalability through horizontal scaling across servers. It supports flexible schemas, full text search, and graph-like connections between data. The document describes OrientDB's products, data model using clusters, Java and RESTful APIs, examples using records and POJOs, and security features.
Invited talk at USEWOD2014 (http://people.cs.kuleuven.be/~bettina.berendt/USEWOD2014/)
A tremendous amount of machine-interpretable information is available in the Linked Open Data Cloud. Unfortunately, much of this data remains underused as machine clients struggle to use the Web. I believe this can be solved by giving machines interfaces similar to those we offer humans, instead of separate interfaces such as SPARQL endpoints. In this talk, I'll discuss the Linked Data Fragments vision on machine access to the Web of Data, and indicate how this impacts usage analysis of the LOD Cloud. We all can learn a lot from how humans access the Web, and those strategies can be applied to querying and analysis. In particular, we have to focus first on solving those use cases that humans can do easily, and only then consider tackling others.
CouchApps are web applications built using CouchDB, JavaScript, and HTML5. CouchDB is a document-oriented database that stores JSON documents, has a RESTful HTTP API, and is queried using map/reduce views. This talk will answer your basic questions about CouchDB, but will focus on building CouchApps and related tools.
This document introduces CouchDB, a document-oriented NoSQL database. It discusses that CouchDB stores flexible JSON documents without a predefined schema, uses JavaScript MapReduce queries, and has a RESTful API. It also provides examples of creating a CouchDB database in Perl, inserting documents, designing views, and querying views.
ArangoDB is an open source multi-model NoSQL database that can be used as a document store, key-value store, and graph database. It provides a query language called AQL that is similar to SQL. Documents and data can be easily extended and manipulated using JavaScript. ArangoDB is highly performant, space efficient, and can scale horizontally. It has been in development since 2011 with the goal of providing a full-featured database while avoiding the downsides of other NoSQL solutions.
The document discusses query mechanisms for NoSQL databases. It begins by describing how relational databases require normalization of data into tables and use SQL for queries. NoSQL databases are introduced as being non-relational, schema-free, and having simple APIs. Document stores are highlighted as a type of NoSQL database that can natively store hierarchical data without normalization. Specific document stores like CouchDB and MongoDB are described, showing how data can be stored and queried in documents through HTTP requests or a mongo client. Map-reduce functions are also discussed as a way to perform complex queries across collections of documents.
A Graph Database That Scales - ArangoDB 3.7 Release WebinarArangoDB Database
örg Schad (Head of Engineering and ML) and Chris Woodward (Developer Relations Engineer) introduce the new capabilities to work with graph in a distributed setting. In addition explain and showcase the new fuzzy search within ArangoDB's search engine as well as JSON schema validation.
Get started with ArangoDB: https://www.arangodb.com/arangodb-tra...
Explore ArangoDB Cloud for free with 1-click demos: https://cloud.arangodb.com/home
ArangoDB is a native multi-model database written in C++ supporting graph, document and key/value needs with one engine and one query language. Fulltext search and ranking is supported via ArangoSearch the fully integrated C++ based search engine in ArangoDB.
OrientDB: Unlock the Value of Document Data RelationshipsFabrizio Fortino
a) A general introduction of graph databases and OrientDB,
b) Why connected data has more value than just data,
c)How to "have fun" with OrientDB combining documents with graphs via SQL,
d) A use case on how OrientDB has helped to raise standards in Irish Public Office.
On OrientDB: NOSQL document databases provide an elegant way to deal with data in different shapes enabling developers to create better and faster products quickly. The main goal of these systems is to find the most efficient solution to manage data itself. With the Big Data Explosion we need to deal with a myriad of highly interconnected information. The challenge now is not only on how to store data but on how to manage, analyse, traverse and use your data within the context of relationships. Graph databases shine at maintaining highly connected data and is the fastest growing category in database management systems: 2014 registered an increase of 250% in terms of adoption and Forrester Research predicts that more than a quarter of enterprises will be using graphs by 2017. OrientDB combines more than one NOSQL model offering the unique flexibility of modelling data in the form of either documents, or graphs, while incorporating object oriented programming as a way of encapsulating relationships.
The document discusses OrientDB, a document-graph database. It provides an overview of key OrientDB concepts like documents, vertices, edges, classes, clusters, and properties. It also compares the relational and graph data models. The presentation was given by Greg McCarvell and introduces Node.js integration with OrientDB through examples.
This document discusses connecting an iOS app to a REST API. It covers using a networking library like AFNetworking to make requests, parsing JSON responses, storing data locally using Core Data, and libraries like RestKit that integrate these steps by mapping JSON to Core Data entities and handling background threading. Authentication using OAuth is also briefly mentioned.
Skype uses PostgreSQL for over 100 database servers and 200 databases to support its online services. It partitions data across multiple databases for scalability and uses tools like pgBouncer, PL/Proxy, SkyTools, PgQ, and Londiste to connect, load balance, and replicate data between databases. This complex database architecture has allowed Skype to grow significantly while remaining easy to manage.
Solid pods and the future of the spatial webKurt Cagle
This document discusses Solid Pods and their potential role in the future of the spatial web. Solid Pods are small, deployable graph databases that follow the principles of the Solid project, including allowing individuals to own and have granular control over their data. Solid Pods address issues that limited the adoption of earlier semantic web efforts. They could store scene graphs, serve as data catalogs, support distributed ledgers, and more. As graph databases, Pods are well-suited to power spatial applications through capabilities like hosting knowledge graphs and serving as intermediate calculation nodes. Standards bodies are exploring how Spatial Web specifications could adopt and extend the Solid Pod architecture.
This is a comprehensive slide on implementing web service in iOS . There are basic information on Web Service . There are steps of using web service in iOS. The presentation emphasized on XML Parsing .
The document discusses fetching and parsing web content in iOS applications. It covers using NSURLConnection to fetch HTTP content, parsing XML with NSXMLParser and third party libraries, and parsing JSON with NSJSONSerialization. Options for XML parsing include SAX and DOM approaches, and common third party XML parsing libraries are mentioned. Examples of fetching weather data from a web service in JSON format are also provided.
Mubashar Iqbal presented on PostgreSQL, an open-source object-relational database system. PostgreSQL prioritizes reliability, security, and standards compliance. It supports Linux, Unix, Windows and is programmed through interfaces like C/C++, Java, .NET, PHP and Python. Common uses include ERP, data warehousing, and network tools. Prominent users include Yahoo, Sony, Reddit, and Skype. Key features include ACID compliance, online backup, point-in-time recovery, and SSL encryption.
Column-oriented databases store data by column rather than by row. This allows fast retrieval of entire columns of data with one read operation. Column-oriented databases are well-suited for analytical queries that retrieve many rows but only a few columns, as only the needed columns are read from disk. Row-oriented databases are better for transactional queries that retrieve or update individual rows. The type of data storage - row-oriented or column-oriented - depends on the types of queries that will be run against the data.
Tutorial on RDFa, to be held at ISWC2010 in Shanghai, China. (I was supposed to hold the tutorial but last minute issues made it impossible for me to travel there...)
ODTUG Webcast - Thinking Clearly about XMLMarco Gralike
Presentation slides used during ODTUG Webcast on the 19th of January explaining first steps in Oracle XMLDB (including extended demo's)
https://www3.gotomeeting.com/register/660686966
This document discusses OrientDB, an open source NoSQL document database. It provides high performance and scalability through horizontal scaling across servers. It supports flexible schemas, full text search, and graph-like connections between data. The document describes OrientDB's products, data model using clusters, Java and RESTful APIs, examples using records and POJOs, and security features.
Invited talk at USEWOD2014 (http://people.cs.kuleuven.be/~bettina.berendt/USEWOD2014/)
A tremendous amount of machine-interpretable information is available in the Linked Open Data Cloud. Unfortunately, much of this data remains underused as machine clients struggle to use the Web. I believe this can be solved by giving machines interfaces similar to those we offer humans, instead of separate interfaces such as SPARQL endpoints. In this talk, I'll discuss the Linked Data Fragments vision on machine access to the Web of Data, and indicate how this impacts usage analysis of the LOD Cloud. We all can learn a lot from how humans access the Web, and those strategies can be applied to querying and analysis. In particular, we have to focus first on solving those use cases that humans can do easily, and only then consider tackling others.
CouchApps are web applications built using CouchDB, JavaScript, and HTML5. CouchDB is a document-oriented database that stores JSON documents, has a RESTful HTTP API, and is queried using map/reduce views. This talk will answer your basic questions about CouchDB, but will focus on building CouchApps and related tools.
This document introduces CouchDB, a document-oriented NoSQL database. It discusses that CouchDB stores flexible JSON documents without a predefined schema, uses JavaScript MapReduce queries, and has a RESTful API. It also provides examples of creating a CouchDB database in Perl, inserting documents, designing views, and querying views.
ArangoDB is an open source multi-model NoSQL database that can be used as a document store, key-value store, and graph database. It provides a query language called AQL that is similar to SQL. Documents and data can be easily extended and manipulated using JavaScript. ArangoDB is highly performant, space efficient, and can scale horizontally. It has been in development since 2011 with the goal of providing a full-featured database while avoiding the downsides of other NoSQL solutions.
The document discusses the alignment between Domain Driven Design (DDD) and NoSQL databases. It explains key DDD concepts like entities, value objects, aggregates, and associations, and how they map to constructs in document databases, graph databases, and multi-model databases. The document concludes that DDD and multi-model NoSQL databases are well-suited for each other, as both advocate for a shared language between technical and business teams and allow modeling of complex domains.
The document summarizes the multi-purpose NoSQL database ArangoDB. It describes ArangoDB as a second generation database that is open source, free, and supports multiple data models including documents, graphs, and key-value. It highlights main features such as being extensible through JavaScript, having high performance, and being easy to use through its web interface and query language AQL.
Graph Database Management Systems provide an effective
and efficient solution to data storage in current scenarios
where data are more and more connected, graph models are
widely used, and systems need to scale to large data sets.
In this framework, the conversion of the persistent layer of
an application from a relational to a graph data store can
be convenient but it is usually an hard task for database
administrators. In this paper we propose a methodology
to convert a relational to a graph database by exploiting
the schema and the constraints of the source. The approach
supports the translation of conjunctive SQL queries over the
source into graph traversal operations over the target. We
provide experimental results that show the feasibility of our
solution and the efficiency of query answering over the target
database.
Designing and Building a Graph Database Application – Architectural Choices, ...Neo4j
Ian closely looks at design and implementation strategies you can employ when building a Neo4j-based graph database solution, including architectural choices, data modelling, and testing.g
Working With a Real-World Dataset in Neo4j: Import and ModelingNeo4j
This webinar will cover how to work with a real world dataset in Neo4j, with a focus on how to build a graph from an existing dataset (in this case a series of JSON files). We will explore how to performantly import the data into Neo4j - both in the case of an initial import and scaling writes for your graph application. We will demonstrate different approaches for data import (neo4j-import, LOAD CSV, and using the official Neo4j drivers), and discuss when it makes to use each import technique. If you've ever asked these questions, then this webinar is for you!
- How do I design a property graph model for my domain?
- How do I use the official Neo4j drivers?
- How can I deal with concurrent writes to Neo4j?
- How can I import JSON into Neo4j?
Max De Marzi gave an introduction to graph databases using Neo4j as an example. He discussed trends in big, connected data and how NoSQL databases like key-value stores, column families, and document databases address these trends. However, graph databases are optimized for interconnected data by modeling it as nodes and relationships. Neo4j is a graph database that uses a property graph data model and allows querying and traversal through its Cypher query language and Gremlin scripting language. It is well-suited for domains involving highly connected data like social networks.
Neo4j Partner Tag Berlin - Potential für System-Integratoren und Berater Neo4j
This document summarizes a Neo4j partner event. It includes an agenda with sessions on the business potential of Neo4j for system integrators and consultants, the Neo4j partner program, and a case study on using Neo4j to analyze the Panama Papers. There are also sessions on quickly gaining value from Neo4j and on modeling logistics processes with Neo4j.
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A native graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL.
This webinar explains why companies are shifting away from RDBMS towards graphs to unlock the business value in their data relationships.
Reveal.js is an HTML presentation framework that allows users to create beautiful presentations using HTML. It has features like vertical slides, nested slides, Markdown support, different transition styles, themes, slide backgrounds, images, video, tables, quotes, and linking between slides. Presentations can be exported to PDF and custom states and events can be triggered on each slide. The framework is touch optimized and works on devices like mobile phones and tablets.
This document discusses graph databases and provides examples of how the Neo4j graph database can be used. It shows how Neo4j supports social, spatial, financial and other types of connected data. It also summarizes Neo4j's REST API, support for object-oriented programming, routing algorithms, multiple indexes, recommendation systems, and other use cases. The document advocates for graph databases for any problem involving multiple relationships and connections between entities.
This document provides an overview of JavaScript reversing techniques. It discusses JavaScript technologies like the DOM, Ajax, and JSON. It covers security aspects like the same-origin policy. It provides tips for analyzing JavaScript using tools like Firebug. It also demonstrates finding vulnerabilities like DOM-based XSS and reversing obfuscated JavaScript.
Ajax is the web's hottest user interface. Struts is Java's most popular web framework. What happens when we put Ajax on Struts?
In this session, we look at writing a new Struts 2 application from square one, using the Yahoo User Interface (YUI) Library on the front end, and Struts 2 on the backend. YUI provides the glitz and the glamour, and Struts 2 provides the dreary business logic, input validation, and text formatting.
During the session, we will cover
* How to integrate an Ajax UI with Struts 2
* Basics of the Yahoo User Interface (YUI) Library
* Business services Struts can provide to an Ajax UI
Who should attend: Ajax developers who would like to utilize Struts as a back-end, and Struts developers who would like to utilize Ajax as a front-end.
To get the most from this session, some familiarity with an Ajax library, like YUI or Dojo, is helpful.
Lets look at writing a new Struts 2 application from square one, using the Yahoo User Interface (YUI) Library on the front end, and Struts 2 on the backend. YUI provides the glitz and the glamour, and Struts 2 provides the dreary business logic, input validation, and text formatting.
Dart is a new language for the web, enabling you to write JavaScript on a secure and manageable way. No need to worry about "JavaScript: The bad parts".
This presentation concentrates on the developer experience converting from the Java based GWT to Dart.
This document discusses Elasticsearch and how to implement it beyond basic usage covered in Railscasts episodes. It covers Elasticsearch features like being schemaless, distributed, and RESTful. It then discusses how to configure mappings and analyzers for indexing partial words. Examples are given for searching, sorting results, and keeping the index in sync with database changes. Resources for further reading are also provided.
aRangodb, un package per l'utilizzo di ArangoDB con RGraphRM
Lingua talk: Italiano.
Descrizione:
In questo talk parleremo di come integrare e utilizzare ArangoDB, un database multi-modello con supporto nativo ai grafi, con R. Presenteremo quindi aRangodb, il package che abbiamo sviluppato per interfacciarsi in modo più semplice e intuitivo al database. Nel corso del talk mostreremo come il package possa essere utilizzato in ambito data science usando alcuni case studies concreti.
Speaker:
Gabriele Galatolo - Data Scientist - Kode srl
This document provides an overview of JavaScript and jQuery. It covers JavaScript syntax, values, operators, expressions, keywords, comments, objects, functions, conditions, arrays, and the Date object. It also discusses using JavaScript for dynamic web pages, DOM manipulation, and DHTML. Additionally, it provides examples of simple JavaScript programs for adding numbers and using prompt boxes. jQuery is also listed as a topic covered but not described.
This document provides an overview of Angular and TypeScript. It begins with an introduction to Angular and its features like cross-platform support, speed, productivity tools, and full development story. It then compares Angular, AngularJS, and React. Next it discusses tools like NodeJS, Angular CLI, and Visual Studio Code. It covers TypeScript fundamentals like data types, variables, functions, tuples, unions, interfaces, classes, namespaces and modules. It explains Angular architecture components like components, directives, routes, services and NgModule. Finally, it wraps up with a discussion of components in Angular and the topics that will be covered in the next session.
Swagger is a simple yet powerful representation of your RESTful API. With the largest ecosystem of API tooling on the planet, thousands of developers are supporting Swagger in almost every modern programming language and deployment environment. With a Swagger-enabled API, you get interactive documentation, client SDK generation and discoverability.
The document provides security tips and best practices for building web applications in Go. It discusses Go's type system, concurrency model, and standard library features. It also summarizes common vulnerabilities like SQL injection and XSS, and recommends using parameterized queries and HTML escaping to prevent them. Finally, it highlights tools like Gorilla and Gin web frameworks, and techniques like rate limiting and secure cookies to build secure Go applications.
Bringing your app to the web with Dart - Chris Buckett (Entity Group)jaxLondonConference
Presented at JAX London 2013
Building complex applications in the browser is hard especially when you are working in teams. Dart is ideal for developing the next generation of web applications in an enterprise environment, by allowing you to communicate type information to your fellow developers and automated tools. With familiar (but lightweight) syntax, class-based OOP and a type system that allows tooling, Java developers will quickly feel at home with Dart.
Stop the noise! - Introduction to the JSON:API specification in DrupalBjörn Brala
If you’ve ever argued about the way your JSON responses should be formatted, JSON:API can be your anti-bikeshedding tool. JSON:API is a great way to expose a consistent API in your application.
In this session, we will talk about how JSON:API got to where it is today and how it can help you make Drupal the core of all your online transactions. We will check out the specifications and look at the main benefits of JSON:API and see how Drupal implemented the spec.
Expect to learn the structure and features of the JSON:API specifications and why it should be your smart default. You should be able to get started right away with some examples we will provide in this session.
Introduction to Spark Datasets - Functional and relational together at lastHolden Karau
Spark Datasets are an evolution of Spark DataFrames which allow us to work with both functional and relational transformations on big data with the speed of Spark.
This document provides an introduction and overview of the Go programming language and how to build a backend API with Go and connect it to a React frontend. It discusses why Go was created, its core values and uses. It then covers how to install Go, write a basic Go program, and build a RESTful backend API with Gorilla Mux that can return JSON or XML. It also demonstrates connecting a React frontend application to the Go backend using Axios to fetch and display student data. The document encourages asking questions and building a real application with Go and React.
The document provides an overview of the Django web framework's documentation. It outlines the essential documentation sections for getting started, including the Django overview, installation guide, tutorial, and FAQs. It also describes the reference sections that cover various Django features like models, templates, forms, testing, and add-ons. The document recommends reading the essential documentation first before exploring the other reference sections as needed.
The document provides an introduction to getting started with the Ember.js framework. It discusses Ember's core concepts like the application object, naming conventions, routes, templates, models, and controllers. It recommends leveraging existing frameworks like jQuery and Handlebars. The document also introduces some key members of Ember's experienced team and recommends resources like the Ember Inspector and Ember online learning for learning more.
The document discusses compilers and web applications. It begins by stating that writing web applications involves many technologies like HTML, CSS, JavaScript frameworks, databases, and more. In contrast, writing a compiler mainly involves processing source code through phases like lexing, parsing, type checking, and code generation. The document focuses on the code generation and semantic analysis phases of compilers. It provides examples of Crystal code for a compiler and explains key concepts like the Program object that holds compiled program data.
The document discusses the phases of a compiler and analyzing source code semantically. It explains that semantic analysis involves processing the abstract syntax tree (AST) to perform type checking and declaration of types, methods, etc. The key phases are the top-level phase which declares classes, modules, and other top-level items, and the semantic visitor which analyzes nodes in the AST while tracking the current type and looking up declarations.
ATO 2022 - Machine Learning + Graph Databases for Better Recommendations (3)....ArangoDB Database
This document summarizes techniques for combining machine learning and graph databases for better recommendations. It discusses using collaborative filtering with AQL, content-based recommendations with TFIDF and FAISS, and graph neural networks with PyTorch. The document also describes an ArangoFlix demo project that combines these techniques on a movie recommendation system using ArangoDB as the backend graph database.
Note: You have to download the slides and use either powerpoint or google slides to make the links clickable.
Machine Learning + Graph Databases for Better Recommendations
Presented by Chris Woodward
Note: You have to download the slides and use either powerpoint or google slides to make the links clickable.
Machine Learning + Graph Databases for Better Recommendations
Presented by Chris Woodward
The ArangoML Group had a detailed discussion on the topic "GraphSage Vs PinSage" where they shared their thoughts on the difference between the working principles of two popular Graph ML algorithms. The following slidedeck is an accumulation of their thoughts about the comparison between the two algorithms.
Webinar: ArangoDB 3.8 Preview - Analytics at Scale ArangoDB Database
The ArangoDB community and team are proud to preview the next version of ArangoDB, an open-source, highly scalable graph database with multi-model capabilities. Join our CTO, Jörg Schad, Ph.D. and Developer Relation Engineer Chris Woodward in this webinar to learn more about ArangoDB 3.8 and the roadmap for upcoming releases.
This document discusses using graphs and graph databases for machine learning. It provides an overview of graph analytics algorithms that can be used to solve problems with graph data, including recommendations, fraud detection, and network analysis. It also discusses using graph embeddings and graph neural networks for tasks like node classification and link prediction. Finally, it discusses how graphs can be used for machine learning infrastructure and metadata tasks like data provenance, audit trails, and privacy.
These are the slides from the Getting Started with ArangoDB Oasis webinar: https://www.arangodb.com/events/getting-started-with-arangodb-oasis/
Get your own Oasis with a free 14-day trial (no credit card required) at https://cloud.arangodb.com/home.
These are the slides to the webinar about Custom Pregel algorithms in ArangoDB https://youtu.be/DWJ-nWUxsO8. It provides a brief introduction to the capabilities and use cases for Pregel.
Hacktoberfest 2020 'Intro to Knowledge Graph' with Chris Woodward of ArangoDB and reKnowledge. Accompanying video is available here: https://youtu.be/ZZt6xBmltz4
gVisor, Kata Containers, Firecracker, Docker: Who is Who in the Container Space?ArangoDB Database
View the video of this webinar here: https://www.arangodb.com/arangodb-events/gvisor-kata-containers-firecracker-docker/
Containers* have revolutionized the IT landscape and for a long time. Docker seemed to be the default whenever people were talking about containerization technologies**. But traditional container technologies might not be suitable if strong isolation guarantees are required. So recently new technologies such as gVisor, Kata Container, or firecracker have been introduced to close the gap between the strong isolation of virtual machines and the small resource footprint of containers.
In this talk, we will provide an overview of the different containerization technologies, discuss their tradeoffs, and provide guidance for different use cases.
* We will define the term container in more detailed during the talk
** and yes we will also cover some of the pre-docker container space!
We all know good training data is crucial for data scientists to build quality machine learning models. But when productionizing Machine Learning, Metadata is equally important. Consider for example:
- Provenance of model allowing for reproducible builds
- Context to comply with GDPR, CCPA requirements
- Identifying data shift in your production data
This is the reason we built ArangoML Pipeline, a flexible Metadata store which can be used with your existing ML Pipeline.
Today we are happy to announce a release of ArangoML Pipeline Cloud. Now you can start using ArangoML Pipeline without having to even start a separate docker container.
In this webinar, we will show how to leverage ArangoML Pipeline Cloud with your Machine Learning Pipeline by using an example notebook from the TensorFlow tutorial.
Find the video here: https://www.arangodb.com/arangodb-events/arangoml-pipeline-cloud/
Find the recording of this webinar here: https://www.arangodb.com/arangodb-events/3-7-roadmap-performance-at-scale/
After the release of ArangoDB 3.6 we are starting to work on the next version with even more exciting features. As an open-source project we would love to hear your ideas and discuss the roadmap with our community.
Would you like to learn more about Satellite Graphs, Schema Validation, a number of performance and security improvements?
Than join Jörg Schad, Head of Engineering and Machine Learning at ArangoDB, who will share the latest plans for the upcoming ArangoDB 3.7 release as well as the long term roadmap.
The long-awaited Managed Service for ArangoDB is finally here! Users have a fully managed document, graph, and key/value store, plus a search engine, in one place. As we thought of such a powerful service — something that gives you room to breathe, relax, and having someone else taking care of everything —, we called it Oasis.
In this live webinar, Ewout Prangsma, Architect & Teamlead of ArangoDB Oasis, walks you through all the main capabilities of the new service, including high availability, elastic scalability, enterprise-grade security, and also demo the different deployment modes you have at your fingertips.
Before the Q&A part, Ewout also shares what you will be capable of in the future.
The new ArangoDB 3.5 release is here and includes a number of minor and major new features. For example, the ability to perform distributed JOIN operations with SmartJoins, new text search features in ArangoSearch, new consistent backup mechanism, and extended graph database features including k-shortest path queries and the new PRUNE keyword for more efficient queries. Jörg Schad, our Head of Engineering and Machine Learning, will discuss these new features and provide a hands-on demo on how to leverage them for your use case.
This document summarizes new features in ArangoDB version 3.5 including distributed joins, streaming transactions, expanded graph and search capabilities, hot backups, data masking, and time-to-live indexes. It also previews upcoming features like fuzzy search, autocomplete, and faceted search in ArangoSearch as well as k-shortest paths and pruning in graphs.
These are the slides from the webinar, where Chris & Jan walked through the basic concepts, key features and query options you have within ArangoDB as well as discuss scalability considerations for different data models. Chris is the hands-on guy and will showcase a variety of query options you have with a native multi-model database like ArangoDB
In these slides, Jan Steemann, core member of the ArangoDB project, introduced to the idea of native multi-model databases and how this approach can provide much more flexibility for developers, software architects & data scientists.
Running complex data queries in a distributed systemArangoDB Database
With the always-growing amount of data, it is getting increasingly hard to store and get it back efficiently. While the first versions of distributed databases have put all the burden of sharding on the application code, there are now some smarter solutions that handle most of the data distribution and resilience tasks inside the database.
This poses some interesting questions, e.g.
- how are other than by-primary-key queries actually organized and executed in a distributed system, so that they can run most efficiently?
- how do the contemporary distributed databases actually achieve transactional semantics for non-trivial operations that affect different shards/servers?
This talk will give an overview of these challenges and the available solutions that some open source distributed databases have picked to solve them.
Guacamole Fiesta: What do avocados and databases have in common?ArangoDB Database
First, our CTO, Frank Celler, does a quick overview of the latest feature developments and what is new with ArangoDB.
Then, Senior Graph Specialist, Michael Hackstein talks about multi-model database movement, diving deeper into main advantages and technological benefits. He introduces three data-models of ArangoDB (Documents, Graphs and Key-Values) and the reasons behind the technology. We have a look at the ArangoDB Query language (AQL) with hands-on examples. Compare AQL to SQL, see where the differences are and what makes AQL better comprehensible for developers. Finally, we touch the Foxx Microservice framework which allows to easily extend ArangoDB and include it in your microservices landscape.
Crazy Incentives and How They Kill Security. How Do You Turn the Wheel?Christian Folini
Everybody is driven by incentives. Good incentives persuade us to do the right thing and patch our servers. Bad incentives make us eat unhealthy food and follow stupid security practices.
There is a huge resource problem in IT, especially in the IT security industry. Therefore, you would expect people to pay attention to the existing incentives and the ones they create with their budget allocation, their awareness training, their security reports, etc.
But reality paints a different picture: Bad incentives all around! We see insane security practices eating valuable time and online training annoying corporate users.
But it's even worse. I've come across incentives that lure companies into creating bad products, and I've seen companies create products that incentivize their customers to waste their time.
It takes people like you and me to say "NO" and stand up for real security!
Shoehorning dependency injection into a FP language, what does it take?Eric Torreborre
This talks shows why dependency injection is important and how to support it in a functional programming language like Unison where the only abstraction available is its effect system.
Introduction to AI
History and evolution
Types of AI (Narrow, General, Super AI)
AI in smartphones
AI in healthcare
AI in transportation (self-driving cars)
AI in personal assistants (Alexa, Siri)
AI in finance and fraud detection
Challenges and ethical concerns
Future scope
Conclusion
References
Everything You Need to Know About Agentforce? (Put AI Agents to Work)Cyntexa
At Dreamforce this year, Agentforce stole the spotlight—over 10,000 AI agents were spun up in just three days. But what exactly is Agentforce, and how can your business harness its power? In this on‑demand webinar, Shrey and Vishwajeet Srivastava pull back the curtain on Salesforce’s newest AI agent platform, showing you step‑by‑step how to design, deploy, and manage intelligent agents that automate complex workflows across sales, service, HR, and more.
Gone are the days of one‑size‑fits‑all chatbots. Agentforce gives you a no‑code Agent Builder, a robust Atlas reasoning engine, and an enterprise‑grade trust layer—so you can create AI assistants customized to your unique processes in minutes, not months. Whether you need an agent to triage support tickets, generate quotes, or orchestrate multi‑step approvals, this session arms you with the best practices and insider tips to get started fast.
What You’ll Learn
Agentforce Fundamentals
Agent Builder: Drag‑and‑drop canvas for designing agent conversations and actions.
Atlas Reasoning: How the AI brain ingests data, makes decisions, and calls external systems.
Trust Layer: Security, compliance, and audit trails built into every agent.
Agentforce vs. Copilot
Understand the differences: Copilot as an assistant embedded in apps; Agentforce as fully autonomous, customizable agents.
When to choose Agentforce for end‑to‑end process automation.
Industry Use Cases
Sales Ops: Auto‑generate proposals, update CRM records, and notify reps in real time.
Customer Service: Intelligent ticket routing, SLA monitoring, and automated resolution suggestions.
HR & IT: Employee onboarding bots, policy lookup agents, and automated ticket escalations.
Key Features & Capabilities
Pre‑built templates vs. custom agent workflows
Multi‑modal inputs: text, voice, and structured forms
Analytics dashboard for monitoring agent performance and ROI
Myth‑Busting
“AI agents require coding expertise”—debunked with live no‑code demos.
“Security risks are too high”—see how the Trust Layer enforces data governance.
Live Demo
Watch Shrey and Vishwajeet build an Agentforce bot that handles low‑stock alerts: it monitors inventory, creates purchase orders, and notifies procurement—all inside Salesforce.
Peek at upcoming Agentforce features and roadmap highlights.
Missed the live event? Stream the recording now or download the deck to access hands‑on tutorials, configuration checklists, and deployment templates.
🔗 Watch & Download: https://www.youtube.com/live/0HiEmUKT0wY
Slides of Limecraft Webinar on May 8th 2025, where Jonna Kokko and Maarten Verwaest discuss the latest release.
This release includes major enhancements and improvements of the Delivery Workspace, as well as provisions against unintended exposure of Graphic Content, and rolls out the third iteration of dashboards.
Customer cases include Scripted Entertainment (continuing drama) for Warner Bros, as well as AI integration in Avid for ITV Studios Daytime.
Slides for the session delivered at Devoxx UK 2025 - Londo.
Discover how to seamlessly integrate AI LLM models into your website using cutting-edge techniques like new client-side APIs and cloud services. Learn how to execute AI models in the front-end without incurring cloud fees by leveraging Chrome's Gemini Nano model using the window.ai inference API, or utilizing WebNN, WebGPU, and WebAssembly for open-source models.
This session dives into API integration, token management, secure prompting, and practical demos to get you started with AI on the web.
Unlock the power of AI on the web while having fun along the way!
Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...Safe Software
FME is renowned for its no-code data integration capabilities, but that doesn’t mean you have to abandon coding entirely. In fact, Python’s versatility can enhance FME workflows, enabling users to migrate data, automate tasks, and build custom solutions. Whether you’re looking to incorporate Python scripts or use ArcPy within FME, this webinar is for you!
Join us as we dive into the integration of Python with FME, exploring practical tips, demos, and the flexibility of Python across different FME versions. You’ll also learn how to manage SSL integration and tackle Python package installations using the command line.
During the hour, we’ll discuss:
-Top reasons for using Python within FME workflows
-Demos on integrating Python scripts and handling attributes
-Best practices for startup and shutdown scripts
-Using FME’s AI Assist to optimize your workflows
-Setting up FME Objects for external IDEs
Because when you need to code, the focus should be on results—not compatibility issues. Join us to master the art of combining Python and FME for powerful automation and data migration.
Build with AI events are communityled, handson activities hosted by Google Developer Groups and Google Developer Groups on Campus across the world from February 1 to July 31 2025. These events aim to help developers acquire and apply Generative AI skills to build and integrate applications using the latest Google AI technologies, including AI Studio, the Gemini and Gemma family of models, and Vertex AI. This particular event series includes Thematic Hands on Workshop: Guided learning on specific AI tools or topics as well as a prequel to the Hackathon to foster innovation using Google AI tools.
Smart Investments Leveraging Agentic AI for Real Estate Success.pptxSeasia Infotech
Unlock real estate success with smart investments leveraging agentic AI. This presentation explores how Agentic AI drives smarter decisions, automates tasks, increases lead conversion, and enhances client retention empowering success in a fast-evolving market.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
UiPath Automation Suite – Cas d'usage d'une NGO internationale basée à GenèveUiPathCommunity
Nous vous convions à une nouvelle séance de la communauté UiPath en Suisse romande.
Cette séance sera consacrée à un retour d'expérience de la part d'une organisation non gouvernementale basée à Genève. L'équipe en charge de la plateforme UiPath pour cette NGO nous présentera la variété des automatisations mis en oeuvre au fil des années : de la gestion des donations au support des équipes sur les terrains d'opération.
Au délà des cas d'usage, cette session sera aussi l'opportunité de découvrir comment cette organisation a déployé UiPath Automation Suite et Document Understanding.
Cette session a été diffusée en direct le 7 mai 2025 à 13h00 (CET).
Découvrez toutes nos sessions passées et à venir de la communauté UiPath à l’adresse suivante : https://community.uipath.com/geneva/.
Discover the top AI-powered tools revolutionizing game development in 2025 — from NPC generation and smart environments to AI-driven asset creation. Perfect for studios and indie devs looking to boost creativity and efficiency.
https://www.brsoftech.com/ai-game-development.html
An Overview of Salesforce Health Cloud & How is it Transforming Patient CareCyntexa
Healthcare providers face mounting pressure to deliver personalized, efficient, and secure patient experiences. According to Salesforce, “71% of providers need patient relationship management like Health Cloud to deliver high‑quality care.” Legacy systems, siloed data, and manual processes stand in the way of modern care delivery. Salesforce Health Cloud unifies clinical, operational, and engagement data on one platform—empowering care teams to collaborate, automate workflows, and focus on what matters most: the patient.
In this on‑demand webinar, Shrey Sharma and Vishwajeet Srivastava unveil how Health Cloud is driving a digital revolution in healthcare. You’ll see how AI‑driven insights, flexible data models, and secure interoperability transform patient outreach, care coordination, and outcomes measurement. Whether you’re in a hospital system, a specialty clinic, or a home‑care network, this session delivers actionable strategies to modernize your technology stack and elevate patient care.
What You’ll Learn
Healthcare Industry Trends & Challenges
Key shifts: value‑based care, telehealth expansion, and patient engagement expectations.
Common obstacles: fragmented EHRs, disconnected care teams, and compliance burdens.
Health Cloud Data Model & Architecture
Patient 360: Consolidate medical history, care plans, social determinants, and device data into one unified record.
Care Plans & Pathways: Model treatment protocols, milestones, and tasks that guide caregivers through evidence‑based workflows.
AI‑Driven Innovations
Einstein for Health: Predict patient risk, recommend interventions, and automate follow‑up outreach.
Natural Language Processing: Extract insights from clinical notes, patient messages, and external records.
Core Features & Capabilities
Care Collaboration Workspace: Real‑time care team chat, task assignment, and secure document sharing.
Consent Management & Trust Layer: Built‑in HIPAA‑grade security, audit trails, and granular access controls.
Remote Monitoring Integration: Ingest IoT device vitals and trigger care alerts automatically.
Use Cases & Outcomes
Chronic Care Management: 30% reduction in hospital readmissions via proactive outreach and care plan adherence tracking.
Telehealth & Virtual Care: 50% increase in patient satisfaction by coordinating virtual visits, follow‑ups, and digital therapeutics in one view.
Population Health: Segment high‑risk cohorts, automate preventive screening reminders, and measure program ROI.
Live Demo Highlights
Watch Shrey and Vishwajeet configure a care plan: set up risk scores, assign tasks, and automate patient check‑ins—all within Health Cloud.
See how alerts from a wearable device trigger a care coordinator workflow, ensuring timely intervention.
Missed the live session? Stream the full recording or download the deck now to get detailed configuration steps, best‑practice checklists, and implementation templates.
🔗 Watch & Download: https://www.youtube.com/live/0HiEm
RTP Over QUIC: An Interesting Opportunity Or Wasted Time?Lorenzo Miniero
Slides for my "RTP Over QUIC: An Interesting Opportunity Or Wasted Time?" presentation at the Kamailio World 2025 event.
They describe my efforts studying and prototyping QUIC and RTP Over QUIC (RoQ) in a new library called imquic, and some observations on what RoQ could be used for in the future, if anything.