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DBMS > Datomic vs. GeoSpock vs. Netezza

System Properties Comparison Datomic vs. GeoSpock vs. Netezza

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGeoSpock  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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 scaleData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational 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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitewww.datomic.comgeospock.comwww.ibm.com/­products/­netezza
Technical documentationdocs.datomic.com
DeveloperCognitectGeoSpockIBM
Initial release20122000
Current release1.0.6735, June 20232.0, September 2019
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJava, Javascript
Server operating systemsAll OS with a Java VMhostedLinux infoincluded in appliance
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.nono
Secondary indexesyestemporal, categoricalyes
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)yes
APIs and other access methodsRESTful HTTP APIJDBCJDBC
ODBC
OLE DB
Supported programming languagesClojure
Java
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes
TriggersBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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 developmentno
User concepts infoAccess controlnoAccess rights for users can be defined per tableUsers with fine-grained authorization concept

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More resources
DatomicGeoSpockNetezza infoAlso called PureData System for Analytics by IBM
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