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DBMS > Datomic vs. HEAVY.AI vs. Microsoft Azure AI Search vs. PostgreSQL vs. Splice Machine

System Properties Comparison Datomic vs. HEAVY.AI vs. Microsoft Azure AI Search vs. PostgreSQL vs. Splice Machine

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareSearch-as-a-service for web and mobile app developmentWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsSpatial DBMSVector DBMSDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comgithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­en-us/­services/­searchwww.postgresql.orgsplicemachine.com
Technical documentationdocs.datomic.comdocs.heavy.ailearn.microsoft.com/­en-us/­azure/­searchwww.postgresql.org/­docssplicemachine.com/­how-it-works
DeveloperCognitectHEAVY.AI, Inc.MicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerSplice Machine
Initial release2012201620151989 info1989: Postgres, 1996: PostgreSQL2014
Current release1.0.6735, June 20235.10, January 2022V116.3, May 20243.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++ and CUDACJava
Server operating systemsAll OS with a Java VMLinuxhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLnoyesnoyes infostandard with numerous extensionsyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Thrift
Vega
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
All languages supporting JDBC/ODBC/Thrift
Python
C#
Java
JavaScript
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoJava
TriggersBy using transaction functionsnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoRound robinSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashShared 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 replicationyes infoImplicit feature of the cloud serviceSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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 developmentyesnonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardyes infousing Azure authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
DatomicHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure AI SearchPostgreSQLSplice Machine
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