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DBMS > Databricks vs. Netezza vs. PostGIS vs. SWC-DB

System Properties Comparison Databricks vs. Netezza vs. PostGIS vs. SWC-DB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPostGIS  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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.Data warehouse and analytics appliance part of IBM PureSystemsSpatial extension of PostgreSQLA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Relational DBMS
Relational DBMSSpatial DBMSWide column store
Secondary database modelsRelational DBMSTime Series 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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.databricks.comwww.ibm.com/­products/­netezzapostgis.netgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.databricks.compostgis.net/­documentation
DeveloperDatabricksIBMAlex Kashirin
Initial release2013200020052020
Current release3.4.2, February 20240.5, April 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL v2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++
Server operating systemshostedLinux infoincluded in applianceLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
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.yesyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesyesSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
Proprietary protocol
Thrift
Supported programming languagesPython
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C++
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesuser defined functionsno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infobased on PostgreSQLSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infobased on PostgreSQL
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
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 controlUsers with fine-grained authorization conceptyes infobased on PostgreSQL
More information provided by the system vendor
DatabricksNetezza infoAlso called PureData System for Analytics by IBMPostGISSWC-DB infoSuper Wide Column Database
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksNetezza infoAlso called PureData System for Analytics by IBMPostGISSWC-DB infoSuper Wide Column Database
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