Deep Dive on ArangoDB

Deep Dive on ArangoDB

• 1.
  Deep Dive onArangoDB Max Neunhöffer Cologne, 25 February 2016 www.arangodb.com
• 2.
  Overview
• 3.
  is a multi-modelDatabase Features is a document store, a key/value store and a graph database, offers convenient queries (via HTTP/REST and AQL), including joins between different collections, and graph queries, with configurable consistency guarantees using transactions. =⇒ Allows polyglot persistence with multiple instances of a single technology.
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  is extensible byJavaScript Code The Foxx Microservice Framework Allows you to extend the HTTP/REST API by your own routes, which you implement in JavaScript running on the database server, with direct access to the C++ DB engine. Unprecedented possibilities for data centric services: custom-made complex queries or authorizations schema-validation push feeds, etc.
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  is a DataCenter Operating System App These days, computing clusters run Data Center Operating Systems. Idea Distributed applications can be deployed as easily as one installs a mobile app on a phone. Cluster resource management is automatic. This leads to significantly better resource utilization. Fault tolerance, self-healing and automatic failover is guaranteed. runs on Apache Mesos and Mesosphere DCOS clusters.
• 6.
  Details
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  The Multi-Model Approach Multi-modeldatabase A multi-model database combines a document store with a graph database and is at the same time a key/value store, with a common query language for all three data models. Important: is able to compete with specialised products on their turf allows for polyglot persistence using a single database technology In a microservice architecture, there will be several different deployments.
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  Use case: Aircraftfleet management
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  Use case: Aircraftfleet management One of our customers uses ArangoDB to store each part, component, unit or aircraft as a document model containment as a graph thus can easily find all parts of some component keep track of maintenance intervals perform queries orthogonal to the graph structure thereby getting good efficiency for all needed queries http://radar.oreilly.com/2015/07/ data-modeling-with-multi-model-databases.html
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  Why is multi-modelpossible at all? Document stores and key/value stores Document stores: have primary key, are key/value stores. Without using secondary indexes, performance is nearly as good as with opaque data instead of JSON. Good horizontal scalability can be achieved for key lookups. https://www.arangodb.com/2015/10/benchmark-postgresql-mongodb-arangodb/
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  Why is multi-modelpossible at all? Document stores and graph databases Graph database: would like to associate arbitrary data with vertices and edges, so JSON documents are a good choice. A good edge index, giving fast access to neighbours. This can be a secondary index. Graph support in the query language. Implementations of graph algorithms in the DB engine. https://www.arangodb.com/2015/10/benchmark-postgresql-mongodb-arangodb/
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  Powerful query language AQL Thebuilt in Arango Query Language allows complex, powerful and convenient queries, with transaction semantics, allowing to do joins, AQL is independent of the driver used and offers protection against injections by design.
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  Extensible through JavaScript TheFoxx Microservice Framework Allows you to extend the HTTP/REST API by your own routes, which you implement in JavaScript running on the database server, with direct access to the C++ DB engine. Unprecedented possibilities for data centric services: complex queries or authorizations, schema-validation, push feeds, etc. easy deployment via web interface or REST API, automatic API description through Swagger =⇒ discoverability of services.
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  Replication and Sharding ArangoDBprovides (Version 2.8, January 2016) Sharding with automatic data distribution, easy setup of (asynchronous) replication (cluster and single), fault tolerance by automatic failover, full integration with Apache Mesos and Mesosphere DCOS. Work in progress (Version 3.0, March 2016): synchronous replication in cluster mode, zero administration by a self-repairing and self-balancing cluster architecture.
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  horizontal scalability Experiment: Singledocument writes (1kB / doc) on cluster of sizes 8 to 80 machi- nes (64 to 640 vCPUs), another 4 to 40 load servers, running on AWS. https://mesosphere.com/blog/2015/11/30/arangodb-benchmark-dcos/
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  Action
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  First deployment: asimple key/value store A key/value store One collection “data”, indexes on “value” (sorted) and “name” (hash). Single document requests Indexes possible Range queries possible
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  Second deployment: aMicroservice as a Foxx app A Foxx Microservice Simple TODO app, deployed from app store with web UI. REST/JSON API available Swagger generates API description automatically
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  Third deployment: asingle server graph database A Graph Database Graph “worldCountry” with vertex collection “worldVertex” and edge collection “worldEdges”, links from cities to countries to continents to world. Show some graph traversals. Show graph viewer.
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  Fourth deployment: amulti-model application A multi-model database Some data from a web shop. Show some queries.
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  Links https://www.arangodb.com https://docs.arangodb.com/cookbook/index.html https://github.com/ArangoDB/guesser http://mesos.apache.org/ https://mesosphere.com/ https://mesosphere.github.io/marathon/ https://gist.github.com/neunhoef/4f85f4c64ba27df5492f (The last linkis to a github gist with accompanying material.)