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DBMS > Datomic vs. MaxDB vs. Spark SQL vs. SWC-DB

System Properties Comparison Datomic vs. MaxDB vs. Spark SQL vs. SWC-DB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA robust and reliable RDBMS optimized to run all major SAP solutionsSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score2.32
Rank#112  Overall
#55  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.datomic.commaxdb.sap.comspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.datomic.commaxdb.sap.com/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectSAP, acquired from Software AG (Adabas-D) in 1997Apache Software FoundationAlex Kashirin
Initial release2012198420142020
Current release1.0.6735, June 20237.9.10.12, February 20243.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoLimited community edition freeOpen Source infoApache 2.0Open 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, ClojureC++ScalaC++
Server operating systemsAll OS with a Java VMAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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.nononono
Secondary indexesyesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
WebDAV
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesClojure
Java
.Net
C#
Java
Perl
PHP
Python
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesnono
TriggersBy using transaction functionsyesnono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 developmentnonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardno

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More resources
DatomicMaxDB infoformerly named Adabas-DSpark SQLSWC-DB infoSuper Wide Column Database
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