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DBMS > Citus vs. Databricks vs. GeoSpock vs. Google Cloud Bigtable

System Properties Comparison Citus vs. Databricks vs. GeoSpock vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Bigtable  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 scaleGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSKey-value store
Wide column store
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitewww.citusdata.comwww.databricks.comgeospock.comcloud.google.com/­bigtable
Technical documentationdocs.citusdata.comdocs.databricks.comcloud.google.com/­bigtable/­docs
DeveloperDatabricksGeoSpockGoogle
Initial release201020132015
Current release8.1, December 20182.0, September 2019
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava, Javascript
Server operating systemsLinuxhostedhostedhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 functionalityyesnono
Secondary indexesyesyestemporal, categoricalno
SQL infoSupport of SQLyes infostandard, with numerous extensionswith Databricks SQLANSI SQL for query only (using Presto)no
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
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 aggregatesnono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic single-row operations
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 controlfine grained access rights according to SQL-standardAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
CitusDatabricksGeoSpockGoogle Cloud Bigtable
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
CitusDatabricksGeoSpockGoogle Cloud Bigtable
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