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

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatomic  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.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpatial 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.databricks.comwww.datomic.compostgis.netgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.databricks.comdocs.datomic.compostgis.net/­documentation
DeveloperDatabricksCognitectAlex Kashirin
Initial release2013201220052020
Current release1.0.6735, June 20233.4.2, February 20240.5, April 2021
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen 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 languageJava, ClojureCC++
Server operating systemshostedAll OS with a Java VMLinux
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.yesnoyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyesSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIProprietary protocol
Thrift
Supported programming languagesPython
R
Scala
Clojure
Java
C++
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoTransaction Functionsuser defined functionsno
TriggersBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes infobased on PostgreSQLSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersyes infobased on PostgreSQL
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentnono
User concepts infoAccess controlnoyes infobased on PostgreSQL
More information provided by the system vendor
DatabricksDatomicPostGISSWC-DB infoSuper Wide Column Database
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDatomicPostGISSWC-DB infoSuper Wide Column Database
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