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DBMS > Citus vs. Datomic vs. Drizzle vs. Solr

System Properties Comparison Citus vs. Datomic vs. Drizzle vs. Solr

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDatomic  Xexclude from comparisonDrizzle  Xexclude from comparisonSolr  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
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 durabilityMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument storeSpatial 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
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.citusdata.comwww.datomic.comsolr.apache.org
Technical documentationdocs.citusdata.comdocs.datomic.comsolr.apache.org/­resources.html
DeveloperCognitectDrizzle project, originally started by Brian AkerApache Software Foundation
Initial release2010201220082006
Current release8.1, December 20181.0.6735, June 20237.2.4, September 20129.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercial infolimited edition freeOpen Source infoGNU GPLOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava, ClojureC++Java
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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 functionalitynoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoyes infowith proprietary extensionsSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIJDBCJava API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Clojure
Java
C
C++
Java
PHP
.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 FunctionsnoJava plugins
TriggersyesBy using transaction functionsno infohooks for callbacks inside the server can be used.yes 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 peersShardingSharding
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 replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 developmentyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoPluggable authentication mechanisms infoe.g. LDAP, HTTPyes

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More resources
CitusDatomicDrizzleSolr
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