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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonOpenEdge  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityData warehouse and analytics appliance part of IBM PureSystemsApplication 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comwww.ibm.com/­products/­netezzawww.progress.com/­openedgespark.apache.org/­sql
Technical documentationdocs.datomic.comdocumentation.progress.com/­output/­ua/­OpenEdge_latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectIBMProgress Software CorporationApache Software Foundation
Initial release2012200019842014
Current release1.0.6735, June 2023OpenEdge 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScala
Server operating systemsAll OS with a Java VMLinux infoincluded in applianceAIX
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.noyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyesyes infoclose to SQL 92SQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
OLE DB
JDBC
ODBC
JDBC
ODBC
Supported programming languagesClojure
Java
C
C++
Fortran
Java
Lua
Perl
Python
R
Progress proprietary ABL (Advanced Business Language)Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesyesno
TriggersBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardinghorizontal 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 replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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 developmentnono
User concepts infoAccess controlnoUsers with fine-grained authorization conceptUsers and groupsno

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More resources
DatomicNetezza infoAlso called PureData System for Analytics by IBMOpenEdgeSpark SQL
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