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DBMS > GeoSpock vs. Greenplum vs. InfinityDB vs. Spark SQL

System Properties Comparison GeoSpock vs. Greenplum vs. InfinityDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGreenplum  Xexclude from comparisonInfinityDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleAnalytic 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.A Java embedded Key-Value Store which extends the Java Map interfaceSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegeospock.comgreenplum.orgboilerbay.comspark.apache.org/­sql
Technical documentationdocs.greenplum.orgboilerbay.com/­infinitydb/­manualspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockPivotal Software Inc.Boiler Bay Inc.Apache Software Foundation
Initial release200520022014
Current release2.0, September 20197.0.0, September 20234.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJavaScala
Server operating systemshostedLinuxAll OS with a Java VMLinux
OS X
Windows
Data schemeyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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 4.2nono
Secondary indexestemporal, categoricalyesno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLANSI SQL for query only (using Presto)yesnoSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
Supported programming languagesC
Java
Perl
Python
R
JavaJava
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynoyesno infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlAccess rights for users can be defined per tablefine grained access rights according to SQL-standardnono

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More resources
GeoSpockGreenplumInfinityDBSpark SQL
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