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DBMS > Datomic vs. Kinetica vs. NSDb vs. Solr vs. TimesTen

System Properties Comparison Datomic vs. Kinetica vs. NSDb vs. Solr vs. TimesTen

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonSolr  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA widely used distributed, scalable search engine based on Apache LuceneIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSRelational DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.datomic.comwww.kinetica.comnsdb.iosolr.apache.orgwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.datomic.comdocs.kinetica.comnsdb.io/­Architecturesolr.apache.org/­resources.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperCognitectKineticaApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20122012201720061998
Current release1.0.6735, June 20237.1, August 20219.6.0, April 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC, C++Java, ScalaJava
Server operating systemsAll OS with a Java VMLinuxLinux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes infosupports customizable data types and automatic typingyes
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.nononoyesno
Secondary indexesyesyesall fields are automatically indexedyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageSolr Parallel SQL Interfaceyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesClojure
Java
C++
Java
JavaScript (Node.js)
Python
Java
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functionsnoJava pluginsPL/SQL
TriggersBy using transaction functionsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesUsing Apache Luceneyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlnoAccess rights for users and roles on table levelyesfine grained access rights according to SQL-standard

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More resources
DatomicKineticaNSDbSolrTimesTen
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