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DBMS > Datomic vs. GridGain vs. HEAVY.AI

System Properties Comparison Datomic vs. GridGain vs. HEAVY.AI

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGridGain  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGridGain is an in-memory computing platform, built on Apache IgniteA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Websitewww.datomic.comwww.gridgain.comgithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdocs.datomic.comwww.gridgain.com/­docs/­index.htmldocs.heavy.ai
DeveloperCognitectGridGain Systems, Inc.HEAVY.AI, Inc.
Initial release201220072016
Current release1.0.6735, June 2023GridGain 8.5.15.10, January 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava, C++, .NetC++ and CUDA
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
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.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsRESTful HTTP APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Vega
Supported programming languagesClojure
Java
C#
C++
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes (compute grid and cache interceptors can be used instead)no
TriggersBy using transaction functionsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes (replicated cache)Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 developmentyesyes
User concepts infoAccess controlnoSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard

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