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DBMS > Datomic vs. Fujitsu Enterprise Postgres vs. Kinetica

System Properties Comparison Datomic vs. Fujitsu Enterprise Postgres vs. Kinetica

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Fully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitewww.datomic.comwww.postgresql.fastware.comwww.kinetica.com
Technical documentationdocs.datomic.comwww.postgresql.fastware.com/­product-manualsdocs.kinetica.com
DeveloperCognitectPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyKinetica
Initial release20122012
Current release1.0.7075, December 2023Fujitsu Enterprise Postgres 14, January 20227.1, August 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureCC, C++
Server operating systemsAll OS with a Java VMLinux
Windows
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
Java
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functionsuser defined functions
TriggersBy using transaction functionsyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peerspartitioning by range, list and by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 developmentyes infoGPU vRAM or System RAM
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
DatomicFujitsu Enterprise PostgresKinetica
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