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DBMS > Kinetica vs. NSDb vs. Tarantool vs. Tibero

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

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonTarantool  Xexclude from comparisonTibero  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 applicationsA secure RDBMS, designed for easy portability from 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
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Score1.63
Rank#139  Overall
#25  Document stores
#24  Key-value stores
#65  Relational DBMS
Score1.46
Rank#151  Overall
#70  Relational DBMS
Websitewww.kinetica.comnsdb.iowww.tarantool.ious.tmaxsoft.com/­products/­tibero
Technical documentationdocs.kinetica.comnsdb.io/­Architecturewww.tarantool.io/­en/­doctechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperKineticaVKTmaxSoft
Initial release2012201720082003
Current release7.1, August 20212.10.0, May 20227, September 2022
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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++Java, ScalaC and C++C and Assembler
Server operating systemsLinuxLinux
macOS
BSD
Linux
macOS
AIX
HP-UX
Linux
Solaris
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.nononoyes
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)
Tibero CLI
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsnoLua, C and SQL stored proceduresPersistent Stored Procedure (PSM)
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 eventsyes
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.horizontal partitioning infoby range, hash, list or composite
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
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
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 infoplanned for next version
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 (SQL 92, SQL 99)

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More resources
KineticaNSDbTarantoolTibero
DB-Engines blog posts

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

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