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DBMS > Solr vs. TimescaleDB vs. Tkrzw vs. Valentina Server

System Properties Comparison Solr vs. TimescaleDB vs. Tkrzw vs. Valentina Server

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Editorial information provided by DB-Engines
NameSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionA widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetObject-relational database and reports server
Primary database modelSearch engineTime Series DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score42.91
Rank#24  Overall
#3  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitesolr.apache.orgwww.timescale.comdbmx.net/­tkrzwwww.valentina-db.net
Technical documentationsolr.apache.org/­resources.htmldocs.timescale.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software FoundationTimescaleMikio HirabayashiParadigma Software
Initial release2006201720201999
Current release9.6.0, April 20242.15.0, May 20240.9.3, August 20205.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-freeyes
Typing infopredefined data types such as float or dateyes infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesnoyes
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.yesyesno
Secondary indexesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLSolr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntaxnoyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ODBC
Supported programming languages.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C++
Java
Python
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellnoyes
Triggersyes infoUser configurable commands triggered on index changesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infousing specific database classesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
SolrTimescaleDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetValentina Server
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