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DBMS > Databricks vs. PostGIS vs. Spark SQL vs. StarRocks

System Properties Comparison Databricks vs. PostGIS vs. Spark SQL vs. StarRocks

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonPostGIS  Xexclude from comparisonSpark SQL  Xexclude from comparisonStarRocks  Xexclude from comparison
DescriptionThe 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 extension of PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processingAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelDocument store
Relational DBMS
Spatial DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.04
Rank#189  Overall
#88  Relational DBMS
Websitewww.databricks.compostgis.netspark.apache.org/­sqlwww.starrocks.io
Technical documentationdocs.databricks.compostgis.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperDatabricksApache Software FoundationThe Linux Foundation infosince Feb 2023
Initial release2013200520142020
Current release3.4.2, February 20243.5.0 ( 2.13), September 20232.5.3, March 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScalaC++, Java
Server operating systemshostedLinux
OS X
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
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.yesyesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
MySQL protocol
Supported programming languagesPython
R
Scala
Java
Python
R
Scala
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnouser defined functions
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesyes infobased on PostgreSQLyes, utilizing Spark Corehorizontal partitioning (by range and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infobased on PostgreSQLnone
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 integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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 controlyes infobased on PostgreSQLnoRole based access control and fine grained access rights
More information provided by the system vendor
DatabricksPostGISSpark SQLStarRocks
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksPostGISSpark SQLStarRocks
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