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DBMS > Datomic vs. GeoSpock vs. OpenEdge vs. Spark SQL

System Properties Comparison Datomic vs. GeoSpock vs. OpenEdge vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGeoSpock  Xexclude from comparisonOpenEdge  Xexclude from comparisonSpark SQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpatial and temporal data processing engine for extreme data scaleApplication development environment with integrated database management systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
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
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comgeospock.comwww.progress.com/­openedgespark.apache.org/­sql
Technical documentationdocs.datomic.comdocumentation.progress.com/­output/­ua/­OpenEdge_latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectGeoSpockProgress Software CorporationApache Software Foundation
Initial release201219842014
Current release1.0.6735, June 20232.0, September 2019OpenEdge 12.2, March 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJava, JavascriptScala
Server operating systemsAll OS with a Java VMhostedAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyesno
Secondary indexesyestemporal, categoricalyesno
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)yes infoclose to SQL 92SQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBCJDBC
ODBC
JDBC
ODBC
Supported programming languagesClojure
Java
Progress proprietary ABL (Advanced Business Language)Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyesno
TriggersBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersAutomatic shardinghorizontal partitioning infosince Version 11.4yes, utilizing Spark Core
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 integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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 controlnoAccess rights for users can be defined per tableUsers and groupsno

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DatomicGeoSpockOpenEdgeSpark SQL
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