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DBMS > Amazon DocumentDB vs. ArangoDB vs. OrigoDB vs. Quasardb

System Properties Comparison Amazon DocumentDB vs. ArangoDB vs. OrigoDB vs. Quasardb

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonArangoDB  Xexclude from comparisonOrigoDB  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.A fully ACID in-memory object graph databaseDistributed, high-performance timeseries database
Primary database modelDocument storeDocument store
Graph DBMS
Key-value store
Search engine
Document store
Object oriented DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score3.30
Rank#82  Overall
#14  Document stores
#5  Graph DBMS
#10  Key-value stores
#10  Search engines
Score0.00
Rank#385  Overall
#54  Document stores
#21  Object oriented DBMS
Score0.13
Rank#332  Overall
#28  Time Series DBMS
Websiteaws.amazon.com/­documentdbarangodb.comorigodb.comquasar.ai
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.arangodb.comorigodb.com/­docsdoc.quasar.ai/­master
Social network pagesLinkedInTwitterFacebookYouTubeInstagram
DeveloperArangoDB Inc.Robert Friberg et alquasardb
Initial release201920122009 infounder the name LiveDB2009
Current release3.11.5, November 20233.14.1, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial license (Enterprise) availableOpen Sourcecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.
Implementation languageC++C#C++
Server operating systemshostedLinux
OS X
Windows
Linux
Windows
BSD
Linux
OS X
Windows
Data schemeschema-freeschema-free infoautomatically recognizes schema within a collectionyesschema-free
Typing infopredefined data types such as float or dateyesyes infostring, double, boolean, list, hashUser defined using .NET types and collectionsyes infointeger and binary
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono infocan be achieved using .NETno
Secondary indexesyesyesyesyes infowith tags
SQL infoSupport of SQLnononoSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
.NET Client API
HTTP API
LINQ
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
.Net.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoJavaScriptyesno
Triggersnonoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infosince version 2.0horizontal partitioning infoclient side managed; servers are not synchronizedSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replication with configurable replication factorSource-replica replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)no infocan be done with stored procedures in JavaScriptnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes inforelationships in graphsdepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoTransient mode
User concepts infoAccess controlAccess rights for users and rolesyesRole based authorizationCryptographically strong user authentication and audit trail
More information provided by the system vendor
Amazon DocumentDBArangoDBOrigoDBQuasardb
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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More resources
Amazon DocumentDBArangoDBOrigoDBQuasardb
DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
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