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DBMS > AgensGraph vs. Citus vs. GeoSpock vs. Tarantool

System Properties Comparison AgensGraph vs. Citus vs. GeoSpock vs. Tarantool

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonCitus  Xexclude from comparisonGeoSpock  Xexclude from comparisonTarantool  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSpatial and temporal data processing engine for extreme data scaleIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeTime Series DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitebitnine.net/­agensgraphwww.citusdata.comgeospock.comwww.tarantool.io
Technical documentationbitnine.net/­documentationdocs.citusdata.comwww.tarantool.io/­en/­doc
DeveloperBitnine Global Inc.GeoSpockVK
Initial release201620102008
Current release2.1, December 20188.1, December 20182.0, September 20192.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoAGPL, commercial license also availablecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCCJava, JavascriptC and C++
Server operating systemsLinux
OS X
Windows
LinuxhostedBSD
Linux
macOS
Data schemedepending on used data modelyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.noyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyestemporal, categoricalyes
SQL infoSupport of SQLyesyes infostandard, with numerous extensionsANSI SQL for query only (using Presto)Full-featured ANSI SQL support
APIs and other access methodsCypher Query Language
JDBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCOpen binary protocol
Supported programming languagesC
Java
JavaScript
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noLua, C and SQL stored procedures
Triggersnoyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingAutomatic shardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users can be defined per tableAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
AgensGraphCitusGeoSpockTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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