ArangoDB
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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.
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{
"type": "2nd generation NoSQL database",
"model": [ "document", "graph", "key-value" ],
"openSource": true,
"license“: "apache 2",
"version": [ "1.3 stable", "1.4 alpha" ],
"builtWith": [ "C", "C++", "JS" ],
"uses": [ "Google V8" ],
"mainFeatures": [
"Multi-Collection-Transaction",
"Foxx API Framework",
"ArangoDB Query Language",
"Various Indexes",
"API Server",
"Automatic Schema Recognition"
]
}
43](https://image.slidesharecdn.com/arangodbv3-shortcopy-140522223653-phpapp02/85/ArangoDB-43-320.jpg)
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Machine Learning + Graph Databases for Better Recommendations V1 08/06/2022
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ArangoDB 3.9 - Further Powering Graphs at Scale
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GraphSage vs Pinsage #InsideArangoDB
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Webinar: ArangoDB 3.8 Preview - Analytics at Scale
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Hacktoberfest 2020 - Intro to Knowledge Graphs
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gVisor, Kata Containers, Firecracker, Docker: Who is Who in the Container Space?
gVisor, Kata Containers, Firecracker, Docker: Who is Who in the Container Space?ArangoDB Database The document discusses various container technologies and runtimes such as gVisor, Kata Containers, and Firecracker, outlining their architectures and use cases. It emphasizes the importance of container orchestration with Kubernetes, detailing features like scheduling, resource management, and service management. Additionally, it touches on security aspects and the evolution of container technology, urging users to consider their cloud provider and environment when selecting a runtime.
ArangoML Pipeline Cloud - Managed Machine Learning Metadata
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ArangoDB 3.7 Roadmap: Performance at Scale
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Webinar: What to expect from ArangoDB Oasis
Webinar: What to expect from ArangoDB OasisArangoDB Database The document is an agenda for a presentation about ArangoDB Oasis, focusing on its features and deployment models. It covers topics ranging from the transition to Oasis, security enhancements, account management, and future developments. The session also provides guidance on getting started and pricing options for users.
ArangoDB 3.5 Feature Overview Webinar - Sept 12, 2019
ArangoDB 3.5 Feature Overview Webinar - Sept 12, 2019ArangoDB Database The document discusses new features in ArangoDB 3.5, including improvements in the managed cloud service, distributed joins, and new capabilities within ArangoSearch. Notable updates include support for sorted inverted indexes, fuzzy searches, and enhanced graph functionalities. Additionally, it outlines future development plans and resources for further information.
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3.5 webinar ArangoDB Database 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.
Webinar: How native multi model works in ArangoDB
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Are you a Tortoise or a Hare?ArangoDB Database The document discusses performance differences between Google's LevelDB and Facebook's RocksDB, highlighting their target environments: mobile devices versus high-end servers. It presents write operation flows and introduces two algorithms for performance optimization: dynamic pacing and OS scheduler prioritization. The summary emphasizes the importance of self-tuning capabilities in adapting to varying server environments.
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ArangoDB
- 1. 1 Lucas Dohmen @moonbeamlabs ! the multi-purpose NoSQL Database ! www.arangodb.org
- 2. Lucas Dohmen ‣ ArangoDB Core Team ‣ ArangoDB Foxx & Ruby Adapter ‣ Student on the master branch ‣ Open Source Developer & Podcaster 2 / (~( ) ) /_/ ( _-----_(@ @) ( / /|/--| V " " " "
- 3. Why did we start ArangoDB? How should an ideal multi-purpose database look like? Is it already out there? ! ‣ Second Generation NoSQL DB ‣ Unique feature set ‣ Solves some problems of other NoSQL DBs ‣ Greenfield project ‣ Experienced team building NoSQL DBs for more than 10 years 3
- 4. Main Features 4 ‣ Open source and free ‣ Multi model database ‣ Convenient querying ‣ Extendable through JS ‣ High performance & space efficiency ‣ Easy to use ‣ Started in Sep 2011 ‣ Current Version: 2.0
- 5. Free and Open Source ‣ Apache 2 License ‣ On Github ‣ Do what you want with it ‣ ... and don‘t pay a dime! 5
- 6. Multi model database 6 Key/Value Store Document Store Graph Database Source: Andrew Carol Polyglot Persistence
- 7. Key-Value Store ‣ Map value data to unique string keys (identifiers) ‣ Treat data as opaque (data has no structure) ‣ Can implement scaling and partitioning easily due to simplistic data model ‣ Key-value can be seen as a special case of documents. For many applications this is sufficient, but not for all cases. ! ArangoDB ‣ It‘s currently supported as a key-value document. ‣ In the near future it supports special key-value collection. ‣ One of the optimization will be the elimination of JSON in this case, so the value need not be parsed. ‣ Sharding capabilities of Key-Value Collections will differ from Document Collections 7
- 8. Document Store ‣ Normally based on key-value stores (each document still has a unique key) ‣ Allow to save documents with logical similarity in „collections“ ‣ Treat data records as attribute-structured documents (data is no longer opaque) ‣ Often allows querying and indexing document attributes ! ArangoDB ‣ It supports both. A database can contain collections from different types. ‣ For efficient memory handling we have an automatic schema recognition. ‣ It has different ways to retrieve data. CRUD via RESTful Interface, QueryByExample, JS for graph traversals and AQL. 8
- 9. ‣ Example: Computer Science Bibliography ! ! ! ! ! ArangoDB ‣ Supports Property Graphs ‣ Vertices and edges are documents ‣ Query them using geo-index, full-text, SQL-like queries ‣ Edges are directed relations between vertices ‣ Custom traversals and built-in graph algorithms Graph Store 9 Type: inproceeding Title: Finite Size Effects Type: proceeding Title: Neural Modeling Type: person Name:AnthonyC.C. Coolen Label: written Label: published Pages: 99-120 Type: person Name: Snchez-Andrs Label: edited
- 10. Analytic Processing DBsTransaction Processing DBs Managing the evolving state of an IT system Complex Queries Map/Reduce Graphs Extensibility Key/Value Column- Stores Documents Massively Distributed Structured Data NoSQL Map 10
- 11. 11 Transaction Processing DBs Managing the evolving state of an IT system Analytic Processing DBs Map/Reduce Graphs Extensibility Key/Value Column- Stores Complex Queries Documents Massively Distributed Structured Data Another NoSQL Map
- 12. Convenient querying Different scenarios require different access methods: ‣ Query a document by its unique id / key: GET /_api/document/users/12345 ‣ Query by providing an example document: PUT /_api/simple/by-example { "name": "Jan", "age": 38 } ‣ Query via AQL: FOR user IN users FILTER user.active == true RETURN { name: user.name } ‣ Graph Traversals und JS for your own traversals ‣ JS Actions for “intelligent” DB request 12
- 13. Why another query language? 13 ‣ Initially, we implemented a subset of SQL's SELECT ‣ It didn't fit well ‣ UNQL addressed some of the problems ‣ Looked dead ‣ No working implementations ‣ XQuery seemed quite powerful ‣ A bit too complex for simple queries ‣ JSONiq wasn't there when we started
- 14. Other Document Stores ‣ MongoDB uses JSON/BSON as its “query language” ‣ Limited ‣ Hard to read & write for more complex queries ‣ Complex queries, joins and transactions not possible ‣ CouchDB uses Map/Reduces ‣ It‘s not a relational algebra, and therefore hard to generate ‣ Not easy to learn ‣ Complex queries, joins and transactions not possible 14
- 15. Why you may want a more expressive query language 15 Source: http://www.sarahmei.com/blog/2013/11/11/why-you-should-never-use-mongodb/ users friends commenter liker many many many many one one posts comments likes
- 16. users friends commenter liker many many many many one one posts comments likes Why you may want a more expressive query language 16 ‣ Model it as you would in a SQL database ‣ comments gets a commenter_id – then do a join
- 17. users friends commenter liker many many many many one one posts comments likes Why you may want a more expressive query language 17 ‣ Model it as you would in a document store ‣ posts embed comments as an array
- 18. users friends commenter liker many many many many one one posts comments likes Why you may want a more expressive query language 18 ‣ Model it as you would in a graph database ‣ users as nodes, friendships as edges
- 19. ArangoDB Query Language (AQL) 19 ‣ We came up with AQL mid-2012 ‣ Declarative language, loosely based on the syntax of XQuery ‣ Other keywords than SQL so it's clear that the languages are different ‣ Implemented in C and JavaScript
- 20. Example for Aggregation ‣ Retrieve cities with the number of users: FOR u IN users COLLECT city = u.city INTO g RETURN { "city" : city, "numUsersInCity": LENGTH(g) } 20
- 21. Example for Graph Query ‣ Paths: FOR u IN users LET userRelations = ( FOR p IN PATHS( users, relations, "OUTBOUND" ) FILTER p._from == u._id RETURN p ) RETURN { "user" : u, "relations" : userRelations } 21
- 22. Extendable through JS ‣ JavaScript enriches ArangoDB ‣ Multi Collection Transactions ‣ Building small and efficient Apps - Foxx App Framework ‣ Individually Graph Traversals ‣ Cascading deletes/updates ‣ Assign permissions to actions ‣ Aggregate data from multiple queries into a single response ‣ Carry out data-intensive operations ‣ Help to create efficient Push Services - in the near Future 22
- 23. ActionServer-alittleApplicationServer ‣ ArangoDB can answer arbitrary HTTP requests directly ‣ You can write your own JavaScript functions (“actions”) that will be executed server-side ‣ Includes a permission system ! ➡ You can use it as a database or as a combined database/app server 23
- 24. ‣ Single Page Web Applications ‣ Native Mobile Applications ‣ ext. Developer APIs APIs-willbecomemore&moreimportant 24
- 25. ArangoDB Foxx ‣ What if you could talk to the database directly? ‣ It would only need an API. ‣ What if we could define this API in JavaScript? ! ! ! ! ! ! ‣ ArangoDB Foxx is streamlined for API creation – not a jack of all trades ‣ It is designed for front end developers: Use JavaScript, which you already know (without running into callback hell) 25 / (~( ) ) /_/ ( _-----_(@ @) ( / /|/--| V " " " "
- 26. Foxx - Simple Example 26 Foxx = require("org/arangodb/foxx"); ! controller = new Foxx.Controller(appContext); ! controller.get("/users ", function(req, res) { res.json({ hello: }); }); req.params("name"); /:name
- 27. Foxx - More features ‣ Full access to ArangoDB‘s internal APIs: ‣ Simple Queries ‣ AQL ‣ Traversals ‣ Automatic generation of interactive documentation ‣ Models and Repositories ‣ Central repository of Foxx apps for re-use and inspiration ‣ Authentication Module 27
- 28. High performance & space efficiency RAM is cheap, but it's still not free and data volume is growing fast. Requests volumes are also growing. So performance and space efficiency are key features of a multi-purpose database. ! ‣ ArangoDB supports automatic schema recognition, so it is one of the most space efficient document stores. ‣ It offers a performance oriented architecture with a C database core, a C++ communication layer, JS and C++ for additional functionalities. ‣ Performance critical points can be transformed to C oder C++. ‣ Although ArangoDB has a wide range of functions, such as MVCC real ACID, schema recognition, etc., it can compete with popular stores documents. 28
- 29. Space Efficiency ‣ Measure the space on disk of different data sets ‣ First in the standard config, then with some optimization ‣ We measured a bunch of different tasks 29
- 30. Store 50,000 Wiki Articles 30 0 MB 500 MB 1000 MB 1500 MB 2000 MB ArangoDB CouchDB MongoDB Normal Optimized http://www.arangodb.org/2012/07/08/collection-disk-usage-arangodb
- 31. 3,459,421 AOL Search Queries 31 0 MB 550 MB 1100 MB 1650 MB 2200 MB ArangoDB CouchDB MongoDB Normal Optimized http://www.arangodb.org/2012/07/08/collection-disk-usage-arangodb
- 32. Performance: Disclaimer ‣ Always take performance tests with a grain of salt ‣ Performance is very dependent on a lot of factors including the specific task at hand ‣ This is just to give you a glimpse at the performance ‣ Always do your own performance tests (and if you do, report back to us :) ) ‣ But now: Let‘s see some numbers 32
- 33. Execution Time: Bulk Insert of 10,000,000 documents 33 ArangoDB CouchDB MongoDB http://www.arangodb.org/2012/09/04/bulk-inserts-mongodb-couchdb-arangodb
- 34. Conclusion from Tests ‣ ArangoDB is really space efficient ‣ ArangoDB is “fast enough” ‣ Please test it for your own use case 34
- 35. Easy to use ‣ Easy to use admin interface ‣ Simple Queries for simple queries, AQL for complex queries ‣ Simplify your setup: ArangoDB only – no Application Server etc. – on a single server is sufficient for some use cases ‣ You need graph queries or key value storage? You don't need to add another component to the mix. ‣ No external dependencies like the JVM – just install ArangoDB ‣ HTTP interface – use your load balancer 35
- 37. Admin Frontend Collections & Documents 37
- 40. Admin Frontend complete V8 access 40
- 41. ArangoShell 41
- 42. Join the growing community 42 They are working on geo index, full text search and many APIs: Ruby, Python, PHP, Java, Clojure, ...
- 43. ArangoDB.explain() { "type": "2nd generation NoSQL database", "model": [ "document", "graph", "key-value" ], "openSource": true, "license“: "apache 2", "version": [ "1.3 stable", "1.4 alpha" ], "builtWith": [ "C", "C++", "JS" ], "uses": [ "Google V8" ], "mainFeatures": [ "Multi-Collection-Transaction", "Foxx API Framework", "ArangoDB Query Language", "Various Indexes", "API Server", "Automatic Schema Recognition" ] } 43