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DBMS > Kinetica vs. Tarantool vs. TimesTen vs. YottaDB

System Properties Comparison Kinetica vs. Tarantool vs. TimesTen vs. YottaDB

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonTarantool  Xexclude from comparisonTimesTen  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsIn-Memory RDBMS compatible to OracleA fast and solid embedded Key-value store
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS
Relational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extensionRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitewww.kinetica.comwww.tarantool.iowww.oracle.com/­database/­technologies/­related/­timesten.htmlyottadb.com
Technical documentationdocs.kinetica.comwww.tarantool.io/­en/­docdocs.oracle.com/­database/­timesten-18.1yottadb.com/­resources/­documentation
DeveloperKineticaVKOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005YottaDB, LLC
Initial release2012200819982001
Current release7.1, August 20212.10.0, May 202211 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterprisecommercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C and C++C
Server operating systemsLinuxBSD
Linux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Docker
Linux
Data schemeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyesschema-free
Typing infopredefined data types such as float or dateyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyesno
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsFull-featured ANSI SQL supportyesby using the Octo plugin
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Open binary protocolJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C++
Java
PL/SQL
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsLua, C and SQL stored proceduresPL/SQL
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 eventsno
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.none
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)
Multi-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesyes
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 transactionsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyes, write ahead loggingyes infoby means of logfiles and checkpointsyes
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 persistenceyesyes
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
fine grained access rights according to SQL-standardUsers and groups based on OS-security mechanisms

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More resources
KineticaTarantoolTimesTenYottaDB
DB-Engines blog posts

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

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