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DBMS > Datomic vs. FatDB vs. Hive vs. Solr vs. Yaacomo

System Properties Comparison Datomic vs. FatDB vs. Hive vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFatDB  Xexclude from comparisonHive  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA .NET NoSQL DBMS that can integrate with and extend SQL Server.data warehouse software for querying and managing large distributed datasets, built on HadoopA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSSearch 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.datomic.comhive.apache.orgsolr.apache.orgyaacomo.com
Technical documentationdocs.datomic.comcwiki.apache.org/­confluence/­display/­Hive/­Homesolr.apache.org/­resources.html
DeveloperCognitectFatCloudApache Software Foundation infoinitially developed by FacebookApache Software FoundationQ2WEB GmbH
Initial release20122012201220062009
Current release1.0.6735, June 20233.1.3, April 20229.6.0, April 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2Open Source infoApache Version 2commercial
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 languageJava, ClojureC#JavaJava
Server operating systemsAll OS with a Java VMWindowsAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.noyesno
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like DML and DDL statementsSolr Parallel SQL Interfaceyes
APIs and other access methodsRESTful HTTP API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Thrift
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesClojure
Java
C#C++
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infovia applicationsyes infouser defined functions and integration of map-reduceJava plugins
TriggersBy using transaction functionsyes infovia applicationsnoyes 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 peersShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factorselectable replication factoryesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducespark-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
Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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 developmentyesyes
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsAccess rights for users, groups and rolesyesfine grained access rights according to SQL-standard

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More resources
DatomicFatDBHiveSolrYaacomo
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