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DBMS > Citus vs. Datomic vs. HEAVY.AI vs. Kinetica vs. Solr

System Properties Comparison Citus vs. Datomic vs. HEAVY.AI vs. Kinetica vs. Solr

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDatomic  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument storeSpatial DBMSSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.citusdata.comwww.datomic.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comsolr.apache.org
Technical documentationdocs.citusdata.comdocs.datomic.comdocs.heavy.aidocs.kinetica.comsolr.apache.org/­resources.html
DeveloperCognitectHEAVY.AI, Inc.KineticaApache Software Foundation
Initial release20102012201620122006
Current release8.1, December 20181.0.6735, June 20235.10, January 20227.1, August 20219.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercial infolimited edition freeOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava, ClojureC++ and CUDAC, C++Java
Server operating systemsLinuxAll OS with a Java VMLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyesyes infosupports customizable data types and automatic typing
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 functionalitynononoyes
Secondary indexesyesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoyesSQL-like DML and DDL statementsSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Clojure
Java
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoTransaction Functionsnouser defined functionsJava plugins
TriggersyesBy using transaction functionsnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsnone infoBut extensive use of caching in the application peersMulti-source replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardAccess rights for users and roles on table levelyes

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More resources
CitusDatomicHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaSolr
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