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DBMS > Datomic vs. Greenplum vs. Spark SQL

System Properties Comparison Datomic vs. Greenplum vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGreenplum  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score9.23
Rank#47  Overall
#30  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comgreenplum.orgspark.apache.org/­sql
Technical documentationdocs.datomic.comdocs.greenplum.orgspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectPivotal Software Inc.Apache Software Foundation
Initial release201220052014
Current release1.0.6735, June 20237.0.0, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScala
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Windows
Data schemeyesyesyes
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.noyes infosince Version 4.2no
Secondary indexesyesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
ODBC
Supported programming languagesClojure
Java
C
Java
Perl
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesno
TriggersBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingyes, 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 methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 developmentnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardno

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DatomicGreenplumSpark SQL
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