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DBMS > Datomic vs. HEAVY.AI vs. InfinityDB vs. Kinetica vs. Realm

System Properties Comparison Datomic vs. HEAVY.AI vs. InfinityDB vs. Kinetica vs. Realm

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonInfinityDB  Xexclude from comparisonKinetica  Xexclude from comparisonRealm  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 hardwareA Java embedded Key-Value Store which extends the Java Map interfaceFully vectorized database across both GPUs and CPUsA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMSDocument store
Secondary database modelsSpatial DBMSSpatial 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
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Websitewww.datomic.comgithub.com/­heavyai/­heavydb
www.heavy.ai
boilerbay.comwww.kinetica.comrealm.io
Technical documentationdocs.datomic.comdocs.heavy.aiboilerbay.com/­infinitydb/­manualdocs.kinetica.comrealm.io/­docs
DeveloperCognitectHEAVY.AI, Inc.Boiler Bay Inc.KineticaRealm, acquired by MongoDB in May 2019
Initial release20122016200220122014
Current release1.0.6735, June 20235.10, January 20224.07.1, August 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++ and CUDAJavaC, C++
Server operating systemsAll OS with a Java VMLinuxAll OS with a Java VMLinuxAndroid
Backend: server-less
iOS
Windows
Data schemeyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.nonononono
Secondary indexesyesnono infomanual creation possible, using inversions based on multi-value capabilityyesyes
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Thrift
Vega
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
Java
All languages supporting JDBC/ODBC/Thrift
Python
JavaC++
Java
JavaScript (Node.js)
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonouser defined functionsno inforuns within the applications so server-side scripts are unnecessary
TriggersBy using transaction functionsnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoRound robinnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 developmentyesnoyes infoGPU vRAM or System RAMyes infoIn-Memory realm
User concepts infoAccess controlnofine grained access rights according to SQL-standardnoAccess rights for users and roles on table levelyes

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More resources
DatomicHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022InfinityDBKineticaRealm
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