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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonNCache  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 durabilityOpen-Source and Enterprise in-memory Key-Value StoreA widely used distributed, scalable search engine based on Apache LuceneObject-relational database and reports server
Primary database modelRelational DBMSKey-value storeSearch engineRelational DBMS
Secondary database modelsDocument store
Search engine infoUsing distributed Lucene
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.94
Rank#195  Overall
#29  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.datomic.comwww.alachisoft.com/­ncachesolr.apache.orgwww.valentina-db.net
Technical documentationdocs.datomic.comwww.alachisoft.com/­resources/­docssolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperCognitectAlachisoftApache Software FoundationParadigma Software
Initial release2012200520061999
Current release1.0.6735, June 20235.3.3, April 20249.6.0, April 20245.7.5
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoEnterprise Edition availableOpen 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#, .NET, .NET Core, JavaJava
Server operating systemsAll OS with a Java VMLinux
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 schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryes 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 SQLnoSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.Solr Parallel SQL Interfaceyes
APIs and other access methodsRESTful HTTP APIIDistributedCache
JCache
LINQ
Proprietary native API
Java API
RESTful HTTP/JSON API
ODBC
Supported programming languagesClojure
Java
.Net
.Net Core
C#
Java
JavaScript (Node.js)
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 Functionsno infosupport for stored procedures with SQL-Server CLRJava pluginsyes
TriggersBy using transaction functionsyes infoNotificationsyes 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 peersyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes, with selectable consistency levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Eventual Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic locking and pessimistic lockingoptimistic 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 controlnoAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)yesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatomicNCacheSolrValentina Server
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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DatomicNCacheSolrValentina Server
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