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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHBase  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimesTen  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 SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitewww.datomic.comhbase.apache.orgsplicemachine.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.datomic.comhbase.apache.org/­book.htmlsplicemachine.com/­how-it-worksdocs.oracle.com/­database/­timesten-18.1
DeveloperCognitectApache Software Foundation infoApache top-level project, originally developed by PowersetSplice MachineOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2012200820141998
Current release1.0.7075, December 20232.3.4, January 20213.1, March 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache version 2Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaJava
Server operating systemsAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnonoyesyes
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
Thrift
JDBC
Native Spark Datasource
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesClojure
Java
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infoCoprocessors in Javayes infoJavaPL/SQL
TriggersBy using transaction functionsyesyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes infoby means of logfiles and checkpoints
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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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DatomicHBaseSplice MachineTimesTen
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