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DBMS > Citus vs. Coveo vs. Kinetica vs. Tarantool

System Properties Comparison Citus vs. Coveo vs. Kinetica vs. Tarantool

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonCoveo  Xexclude from comparisonKinetica  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentFully vectorized database across both GPUs and CPUsIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSSearch engineRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score2.11
Rank#118  Overall
#11  Search engines
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.citusdata.comwww.coveo.comwww.kinetica.comwww.tarantool.io
Technical documentationdocs.citusdata.comdocs.coveo.comdocs.kinetica.comwww.tarantool.io/­en/­doc
DeveloperCoveoKineticaVK
Initial release2010201220122008
Current release8.1, December 20187.1, August 20212.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, C++C and C++
Server operating systemsLinuxhostedLinuxBSD
Linux
macOS
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, 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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL-like DML and DDL statementsFull-featured ANSI SQL support
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIJDBC
ODBC
RESTful HTTP API
Open binary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
Java
JavaScript
Python
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nouser defined functionsLua, C and SQL stored procedures
Triggersyesyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingyesShardingSharding, 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 replication infoother methods possible by using 3rd party extensionsyesSource-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 methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID, 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 persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardgranular access controls, API key management, content filtersAccess 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

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More resources
CitusCoveoKineticaTarantool
DB-Engines blog posts

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

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