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DBMS > Apache Impala vs. Databricks vs. PostGIS vs. STSdb

System Properties Comparison Apache Impala vs. Databricks vs. PostGIS vs. STSdb

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonPostGIS  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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 PostgreSQLKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSDocument store
Relational DBMS
Spatial DBMSKey-value store
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteimpala.apache.orgwww.databricks.compostgis.netgithub.com/­STSSoft/­STSdb4
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.compostgis.net/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksSTS Soft SC
Initial release2013201320052011
Current release4.1.0, June 20223.4.2, February 20244.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPL v2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC#
Server operating systemsLinuxhostedWindows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)
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.noyesyes
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyesno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
.NET Client API
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C#
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesuser defined functionsno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infobased on PostgreSQLnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes infobased on PostgreSQLnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes infobased on PostgreSQLno
More information provided by the system vendor
Apache ImpalaDatabricksPostGISSTSdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksPostGISSTSdb
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