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DBMS > Datomic vs. NSDb vs. RethinkDB vs. Splice Machine

System Properties Comparison Datomic vs. NSDb vs. RethinkDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonNSDb  Xexclude from comparisonRethinkDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesDBMS for the Web with a mechanism to push updated query results to applications in realtime.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.93
Rank#120  Overall
#59  Relational DBMS
Score0.00
Rank#352  Overall
#33  Time Series DBMS
Score3.23
Rank#90  Overall
#16  Document stores
Score0.71
Rank#210  Overall
#105  Relational DBMS
Websitewww.datomic.comnsdb.iorethinkdb.comsplicemachine.com
Technical documentationdocs.datomic.comnsdb.io/­Architecturerethinkdb.com/­docsdoc.splicemachine.com
DeveloperCognitectThe Linux Foundation infosince July 2017Splice Machine
Initial release2012201720092014
Current release0.9.5951, July 20192.4.1, August 20203.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJava, ScalaC++Java
Server operating systemsAll OS with a Java VMLinux
macOS
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyes infostring, binary, float, bool, date, geometryyes
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 indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like query languagenoyes
APIs and other access methodsRESTful HTTP APIgRPC
HTTP REST
WebSocket
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
Java
Scala
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes infoJava
TriggersBy using transaction functionsClient-side triggers through changefeedsyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding inforange basedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-document operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC basedyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Using Apache Luceneyesyes
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 developmentnoyes
User concepts infoAccess controlnoyes infousers and table-level permissionsAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatomicNSDbRethinkDBSplice Machine
News

How to Break Data Silos to Drive Enterprise-Wide AI
11 June 2021

Point-in-Time Correctness in Machine Learning
1 June 2021

The Compliance Nightmare Lurking in Your Data Science Team
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Whose Job Is It Anyway?
23 April 2021

How Optimizing MLOps Can Revolutionize Enterprise AI
15 April 2021

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