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DBMS > Kinetica vs. NSDb vs. Tarantool vs. TimesTen

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

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonTarantool  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSTime Series DBMSDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score1.67
Rank#150  Overall
#25  Document stores
#25  Key-value stores
#69  Relational DBMS
Score1.35
Rank#165  Overall
#75  Relational DBMS
Websitewww.kinetica.comnsdb.iowww.tarantool.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.kinetica.comnsdb.io/­Architecturewww.tarantool.io/­en/­docdocs.oracle.com/­database/­timesten-18.1
DeveloperKineticaVKOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2012201720081998
Current release7.1, August 20212.10.0, May 202211 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open 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 languageC, C++Java, ScalaC and C++
Server operating systemsLinuxLinux
macOS
BSD
Linux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringstring, 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 indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageFull-featured ANSI SQL supportyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Open binary protocolJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functionsnoLua, 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 nodesShardingShardingSharding, 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
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 configurationEventual 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
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes, write ahead loggingyes infoby means of logfiles and checkpoints
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 persistenceyes
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-standard

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More resources
KineticaNSDbTarantoolTimesTen
DB-Engines blog posts

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

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