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DBMS > Datomic vs. HBase vs. Sphinx vs. Splice Machine

System Properties Comparison Datomic vs. HBase vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHBase  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityWide-column store based on Apache Hadoop and on concepts of BigTableOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSWide column storeSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comhbase.apache.orgsphinxsearch.comsplicemachine.com
Technical documentationdocs.datomic.comhbase.apache.org/­book.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCognitectApache Software Foundation infoApache top-level project, originally developed by PowersetSphinx Technologies Inc.Splice Machine
Initial release2012200820012014
Current release1.0.6735, June 20232.3.4, January 20213.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaC++Java
Server operating systemsAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROnoyes
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
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
Thrift
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infoCoprocessors in Javanoyes infoJava
TriggersBy using transaction functionsyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)noACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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 controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoAccess rights for users, groups and roles according to SQL-standard

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DatomicHBaseSphinxSplice Machine
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