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DBMS > H2 vs. Kinetica vs. Tarantool vs. TigerGraph

System Properties Comparison H2 vs. Kinetica vs. Tarantool vs. TigerGraph

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Editorial information provided by DB-Engines
NameH2  Xexclude from comparisonKinetica  Xexclude from comparisonTarantool  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Fully vectorized database across both GPUs and CPUsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Graph DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitewww.h2database.comwww.kinetica.comwww.tarantool.iowww.tigergraph.com
Technical documentationwww.h2database.com/­html/­main.htmldocs.kinetica.comwww.tarantool.io/­en/­docdocs.tigergraph.com
DeveloperThomas MuellerKineticaVK
Initial release2005201220082017
Current release2.2.220, July 20237.1, August 20212.10.0, May 2022
License infoCommercial or Open SourceOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C and C++C++
Server operating systemsAll OS with a Java VMLinuxBSD
Linux
macOS
Linux
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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 indexesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsFull-featured ANSI SQL supportSQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Open binary protocolGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesJavaC++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C++
Java
Server-side scripts infoStored proceduresJava Stored Procedures and User-Defined Functionsuser defined functionsLua, C and SQL stored proceduresyes
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding, 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 nodesWith clustering: 2 database servers on different computers operate on identical copies of a databaseSource-replica replicationAsynchronous 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 methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 dataACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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 control

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More resources
H2KineticaTarantoolTigerGraph
DB-Engines blog posts

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

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