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DBMS > Datomic vs. Faircom EDGE vs. OrigoDB vs. SpatiaLite vs. Splice Machine

System Properties Comparison Datomic vs. Faircom EDGE vs. OrigoDB vs. SpatiaLite vs. Splice Machine

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpatiaLite  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA fully ACID in-memory object graph databaseSpatial extension of SQLiteOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value store
Relational DBMS
Document store
Object oriented DBMS
Spatial DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comwww.faircom.com/­products/­faircom-edgeorigodb.comwww.gaia-gis.it/­fossil/­libspatialite/­indexsplicemachine.com
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlorigodb.com/­docswww.gaia-gis.it/­gaia-sins/­spatialite_topics.htmlsplicemachine.com/­how-it-works
DeveloperCognitectFairCom CorporationRobert Friberg et alAlessandro FurieriSplice Machine
Initial release201219792009 infounder the name LiveDB20082014
Current release1.0.6735, June 2023V3, October 20205.0.0, August 20203.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availableOpen SourceOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureANSI C, C++C#C++Java
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
Windows
server-lessLinux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL TypesUser defined using .NET types and collectionsyesyes
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 infocan be achieved using .NETno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesnoyesyes
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
HTTP API
LINQ
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.NetC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++yesnoyes infoJava
TriggersBy using transaction functionsyesyes infoDomain Eventsyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning infoclient side managed; servers are not synchronizednoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replicationnoneMulti-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 Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLdepending on modelyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoWrite ahead logyesyes
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 developmentyesyesyesyes
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role based authorizationnoAccess rights for users, groups and roles according to SQL-standard

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More resources
DatomicFaircom EDGE infoformerly c-treeEDGEOrigoDBSpatiaLiteSplice Machine
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