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DBMS > Datomic vs. GridDB vs. Solr vs. Valentina Server

System Properties Comparison Datomic vs. GridDB vs. Solr vs. Valentina Server

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGridDB  Xexclude from comparisonSolr  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable in-memory time series database optimized for IoT and Big DataA widely used distributed, scalable search engine based on Apache LuceneObject-relational database and reports server
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.datomic.comgriddb.netsolr.apache.orgwww.valentina-db.net
Technical documentationdocs.datomic.comdocs.griddb.netsolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperCognitectToshiba CorporationApache Software FoundationParadigma Software
Initial release2012201320061999
Current release1.0.6735, June 20235.1, August 20229.6.0, April 20245.7.5
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Java
Server operating systemsAll OS with a Java VMLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes 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.nonoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)Solr Parallel SQL Interfaceyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
ODBC
Supported programming languagesClojure
Java
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoJava pluginsyes
TriggersBy using transaction functionsyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container leveloptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes 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.yes inforecommended only for testing and developmentyesyesyes
User concepts infoAccess controlnoAccess rights for users can be defined per databaseyesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatomicGridDBSolrValentina Server
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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DatomicGridDBSolrValentina Server
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