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DBMS > Kinetica vs. Tarantool vs. TerminusDB vs. TigerGraph

System Properties Comparison Kinetica vs. Tarantool vs. TerminusDB vs. TigerGraph

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonTarantool  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationshipsA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS
Graph DBMSGraph DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extensionDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.17
Rank#325  Overall
#29  Graph DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitewww.kinetica.comwww.tarantool.ioterminusdb.comwww.tigergraph.com
Technical documentationdocs.kinetica.comwww.tarantool.io/­en/­docterminusdb.github.io/­terminusdb/­#docs.tigergraph.com
DeveloperKineticaVKDataChemist Ltd.
Initial release2012200820182017
Current release7.1, August 20212.10.0, May 202211.0.0, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoGPL V3commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C and C++Prolog, RustC++
Server operating systemsLinuxBSD
Linux
macOS
LinuxLinux
Data schemeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyesyes
Typing infopredefined data types such as float or dateyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyesyes
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.nononono
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsFull-featured ANSI SQL supportSQL-like query language (WOQL)SQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Open binary protocolOWL
RESTful HTTP API
WOQL (Web Object Query Language)
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
JavaScript
Python
C++
Java
Server-side scripts infoStored proceduresuser defined functionsLua, C and SQL stored proceduresyesyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, before/after data modification events, on replication events, client session eventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Graph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Journaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationCasual 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 integrityyesyesyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, cooperative multitaskingyesyes
Durability infoSupport for making data persistentyesyes, write ahead loggingyes infoin-memory journalingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlAccess rights for users and roles on table levelAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Role-based access controlRole-based access control

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More resources
KineticaTarantoolTerminusDB infoformer name was DataChemistTigerGraph
DB-Engines blog posts

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

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