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DBMS > Datomic vs. EJDB vs. Spark SQL vs. STSdb

System Properties Comparison Datomic vs. EJDB vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEJDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
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)Spark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSDocument storeRelational DBMSKey-value store
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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitewww.datomic.comgithub.com/­Softmotions/­ejdbspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.datomic.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectSoftmotionsApache Software FoundationSTS Soft SC
Initial release2012201220142011
Current release1.0.7075, December 20233.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGPLv2Open Source infoApache 2.0Open Source infoGPLv2, 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, ClojureCScalaC#
Server operating systemsAll OS with a Java VMserver-lessLinux
OS X
Windows
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesyes infoprimitive types and user defined types (classes)
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 indexesyesnonono
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIin-process shared libraryJDBC
ODBC
.NET Client API
Supported programming languagesClojure
Java
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonono
TriggersBy using transaction functionsnonono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
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 developmentno
User concepts infoAccess controlnononono

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More resources
DatomicEJDBSpark SQLSTSdb
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