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DBMS > Datomic vs. Dolt vs. Faircom EDGE vs. HEAVY.AI

System Properties Comparison Datomic vs. Dolt vs. Faircom EDGE vs. HEAVY.AI

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDolt  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  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 durabilityA MySQL compatible DBMS with Git-like versioning of data and schemaFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.02
Rank#191  Overall
#89  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Websitewww.datomic.comgithub.com/­dolthub/­dolt
www.dolthub.com
www.faircom.com/­products/­faircom-edgegithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdocs.datomic.comdocs.dolthub.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.heavy.ai
DeveloperCognitectDoltHub IncFairCom CorporationHEAVY.AI, Inc.
Initial release2012201819792016
Current release1.0.7075, December 2023V3, October 20205.10, January 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureGoANSI C, C++C++ and CUDA
Server operating systemsAll OS with a Java VMLinux
macOS
Windows
Android
Linux infoARM, x86
Raspbian
Windows
Linux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyesyes infoANSI SQL queriesyes
APIs and other access methodsRESTful HTTP APICLI Client
HTTP REST
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Supported programming languagesClojure
Java
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infocurrently in alpha releaseyes info.Net, JavaScript, C/C++no
TriggersBy using transaction functionsyesyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneFile partitioning infoCustomizable business rules for partitioningSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.yes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
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 controlnoOnly one user is configurable, and must be specified in the config file at startupFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.fine grained access rights according to SQL-standard

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More resources
DatomicDoltFaircom EDGE infoformerly c-treeEDGEHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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