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DBMS > Kinetica vs. OrigoDB vs. Quasardb vs. Tarantool

System Properties Comparison Kinetica vs. OrigoDB vs. Quasardb vs. Tarantool

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonOrigoDB  Xexclude from comparisonQuasardb  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA fully ACID in-memory object graph databaseDistributed, high-performance timeseries databaseIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSDocument store
Object oriented DBMS
Time Series DBMSDocument store
Key-value store
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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#19  Object oriented DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.kinetica.comorigodb.comquasar.aiwww.tarantool.io
Technical documentationdocs.kinetica.comorigodb.com/­docsdoc.quasar.ai/­masterwww.tarantool.io/­en/­doc
DeveloperKineticaRobert Friberg et alquasardbVK
Initial release20122009 infounder the name LiveDB20092008
Current release7.1, August 20213.14.1, January 20242.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Sourcecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
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#C++C and C++
Server operating systemsLinuxLinux
Windows
BSD
Linux
OS X
Windows
BSD
Linux
macOS
Data schemeyesyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyes infointeger and binarystring, double, decimal, uuid, integer, blob, boolean, datetime
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.nono infocan be achieved using .NETnono
Secondary indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
HTTP API
LINQ
HTTP APIOpen binary protocol
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsyesnoLua, C and SQL stored procedures
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoDomain Eventsnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoclient side managed; servers are not synchronizedSharding infoconsistent hashingSharding, 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 nodesSource-replica replicationSource-replica replicationSource-replica replication with selectable replication factorAsynchronous 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 methodsnonowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate 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
Foreign keys infoReferential integrityyesdepending on modelnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyes infoWrite ahead logyes infoby using LevelDByes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyes infoTransient modeyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users and roles on table levelRole based authorizationCryptographically strong user authentication and audit trailAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
KineticaOrigoDBQuasardbTarantool
DB-Engines blog posts

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

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