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DBMS > Datomic vs. Faircom DB vs. Splice Machine vs. TerminusDB

System Properties Comparison Datomic vs. Faircom DB vs. Splice Machine vs. TerminusDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonSplice Machine  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSGraph DBMS
Secondary database modelsDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.17
Rank#325  Overall
#29  Graph DBMS
Websitewww.datomic.comwww.faircom.com/­products/­faircom-dbsplicemachine.comterminusdb.com
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlsplicemachine.com/­how-it-worksterminusdb.github.io/­terminusdb/­#
DeveloperCognitectFairCom CorporationSplice MachineDataChemist Ltd.
Initial release2012197920142018
Current release1.0.6735, June 2023V12, November 20203.1, March 202111.0.0, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureANSI C, C++JavaProlog, Rust
Server operating systemsAll OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Solaris
Windows
Linux
Data schemeyesschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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 indexesyesyesyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsyesSQL-like query language (WOQL)
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
Native Spark Datasource
ODBC
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesClojure
Java
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++yes infoJavayes
TriggersBy using transaction functionsyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShared Nothhing Auto-Sharding, Columnar PartitioningGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication
Source-replica replication
Journaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Yes, tunable from durable to delayed durability to in-memoryyesyes infoin-memory journaling
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 controlnoFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles according to SQL-standardRole-based access control

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More resources
DatomicFaircom DB infoformerly c-treeACESplice MachineTerminusDB infoformer name was DataChemist
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