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DBMS > Citus vs. Databricks vs. GeoSpock

System Properties Comparison Citus vs. Databricks vs. GeoSpock

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonGeoSpock  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Spatial and temporal data processing engine for extreme data scale
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Websitewww.citusdata.comwww.databricks.comgeospock.com
Technical documentationdocs.citusdata.comdocs.databricks.com
DeveloperDatabricksGeoSpock
Initial release20102013
Current release8.1, December 20182.0, September 2019
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava, Javascript
Server operating systemsLinuxhostedhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes
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.yes infospecific XML type available, but no XML query functionalityyesno
Secondary indexesyesyestemporal, categorical
SQL infoSupport of SQLyes infostandard, with numerous extensionswith Databricks SQLANSI SQL for query only (using Presto)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
JDBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregatesno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
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 persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per table
More information provided by the system vendor
CitusDatabricksGeoSpock
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
CitusDatabricksGeoSpock
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