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DBMS > ArangoDB vs. GridDB vs. Quasardb

System Properties Comparison ArangoDB vs. GridDB vs. Quasardb

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Editorial information provided by DB-Engines
NameArangoDB  Xexclude from comparisonGridDB  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.Scalable in-memory time series database optimized for IoT and Big DataDistributed, high-performance timeseries database
Primary database modelDocument store
Graph DBMS
Key-value store
Search engine
Time Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.32
Rank#90  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitearangodb.comgriddb.netquasar.ai
Technical documentationdocs.arangodb.comdocs.griddb.netdoc.quasar.ai/­master
Social network pagesLinkedInTwitterFacebookYouTubeInstagram
DeveloperArangoDB Inc.Toshiba Corporationquasardb
Initial release201220132009
Current release3.11.5, November 20235.1, August 20223.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial license (Enterprise) availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonono
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 systemsLinux
OS X
Windows
LinuxBSD
Linux
OS X
Windows
Data schemeschema-free infoautomatically recognizes schema within a collectionyesschema-free
Typing infopredefined data types such as float or dateyes infostring, double, boolean, list, hashyes infonumerical, string, blob, geometry, boolean, timestampyes 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
Secondary indexesyesyesyes infowith tags
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language
APIs and other access methodsAQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP API
Supported programming languagesC#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresJavaScriptnono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infosince version 2.0ShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with configurable replication factorSource-replica replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infocan be done with stored procedures in JavaScriptConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobswith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyes inforelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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 controlyesAccess rights for users can be defined per databaseCryptographically strong user authentication and audit trail
More information provided by the system vendor
ArangoDBGridDBQuasardb
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
GitHub trending repository
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
ArangoDBGridDBQuasardb
DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

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