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

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

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonSolr  Xexclude from comparisonSurrealDB  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionFully 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 LuceneA fully ACID transactional, developer-friendly, multi-model DBMSIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSTime Series DBMSSearch engineDocument store
Graph DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.kinetica.comnsdb.iosolr.apache.orgsurrealdb.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.kinetica.comnsdb.io/­Architecturesolr.apache.org/­resources.htmlsurrealdb.com/­docsdocs.oracle.com/­database/­timesten-18.1
DeveloperKineticaApache Software FoundationSurrealDB LtdOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20122017200620221998
Current release7.1, August 20219.6.0, April 2024v1.5.0, May 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Sourcecommercial
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 languageC, C++Java, ScalaJavaRust
Server operating systemsLinuxLinux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
macOS
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-freeyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyes infosupports customizable data types and automatic typingyesyes
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.nonoyesno
Secondary indexesyesall fields are automatically indexedyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSolr Parallel SQL InterfaceSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Java API
RESTful HTTP/JSON API
GraphQL
RESTful HTTP API
WebSocket
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC++
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
Deno
Go
JavaScript (Node.js)
Rust
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functionsnoJava pluginsPL/SQL
Triggersyes 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 nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyesyes 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 infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelyesyes, based on authentication and database rulesfine grained access rights according to SQL-standard

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More resources
KineticaNSDbSolrSurrealDBTimesTen
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