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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisoneXtremeDB  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 durabilityNatively in-memory DBMS with options for persistency, high-availability and clusteringA widely used distributed, scalable search engine based on Apache LuceneObject-relational database and reports server
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Search engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.datomic.comwww.mcobject.comsolr.apache.orgwww.valentina-db.net
Technical documentationdocs.datomic.comwww.mcobject.com/­docs/­extremedb.htmsolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperCognitectMcObjectApache Software FoundationParadigma Software
Initial release2012200120061999
Current release1.0.6735, June 20238.2, 20219.6.0, April 20245.7.5
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2commercial
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 languageJava, ClojureC and C++Java
Server operating systemsAll OS with a Java VMAIX
HP-UX
Linux
macOS
Solaris
Windows
All 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 dateyesyesyes 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.nono infosupport of XML interfaces availableyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoyes infowith the option: eXtremeSQLSolr Parallel SQL Interfaceyes
APIs and other access methodsRESTful HTTP API.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ODBC
Supported programming languagesClojure
Java
.Net
C
C#
C++
Java
Lua
Python
Scala
.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 FunctionsyesJava pluginsyes
TriggersBy using transaction functionsyes infoby defining eventsyes 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 peershorizontal partitioning / shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyes
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 controlnoyesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatomiceXtremeDBSolrValentina Server
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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DatomiceXtremeDBSolrValentina Server
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