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DBMS > Datomic vs. EJDB vs. IRONdb vs. Splice Machine

System Properties Comparison Datomic vs. EJDB vs. IRONdb vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEJDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEmbeddable document-store database library with JSON representation of queries (in MongoDB style)A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.datomic.comgithub.com/­Softmotions/­ejdbwww.circonus.com/solutions/time-series-database/splicemachine.com
Technical documentationdocs.datomic.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.circonus.com/irondb/category/getting-startedsplicemachine.com/­how-it-works
DeveloperCognitectSoftmotionsCirconus LLC.Splice Machine
Initial release2012201220172014
Current release1.0.7075, December 2023V0.10.20, January 20183.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGPLv2commercialOpen 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, ClojureCC and C++Java
Server operating systemsAll OS with a Java VMserver-lessLinuxLinux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes infotext, numeric, histogramsyes
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.nono
Secondary indexesyesnonoyes
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)yes
APIs and other access methodsRESTful HTTP APIin-process shared libraryHTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes, in Luayes infoJava
TriggersBy using transaction functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneAutomatic, metric affinity per nodeShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneconfigurable replication factor, datacenter awareMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes, multi-version concurrency control (MVCC)
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 developmentnoyes
User concepts infoAccess controlnononoAccess rights for users, groups and roles according to SQL-standard

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More resources
DatomicEJDBIRONdbSplice Machine
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