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DBMS > DataFS vs. Datomic vs. HEAVY.AI

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

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonDatomic  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Datomic 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 hardware
Primary database modelObject oriented DBMSRelational DBMSRelational DBMS
Secondary database modelsGraph DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Websitenewdatabase.comwww.datomic.comgithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdev.mobiland.com/­Overview.xspdocs.datomic.comdocs.heavy.ai
DeveloperMobiland AGCognitectHEAVY.AI, Inc.
Initial release201820122016
Current release1.1.263, October 20221.0.6735, June 20235.10, January 2022
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++ and CUDA
Server operating systemsWindowsAll OS with a Java VMLinux
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyes
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.nonono
Secondary indexesnoyesno
SQL infoSupport of SQLnonoyes
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
RESTful HTTP APIJDBC
ODBC
Thrift
Vega
Supported programming languages.Net
C
C#
C++
VB.Net
Clojure
Java
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsno
Triggersno, except callback-events from server when changes happenedBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemnone infoBut extensive use of caching in the application peersSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
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 persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes
User concepts infoAccess controlWindows-Profilenofine grained access rights according to SQL-standard

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