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DBMS > Databricks vs. Datomic vs. Postgres-XL

System Properties Comparison Databricks vs. Datomic vs. Postgres-XL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonPostgres-XL  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 durabilityBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score0.52
Rank#256  Overall
#117  Relational DBMS
Websitewww.databricks.comwww.datomic.comwww.postgres-xl.org
Technical documentationdocs.databricks.comdocs.datomic.comwww.postgres-xl.org/­documentation
DeveloperDatabricksCognitect
Initial release201320122014 infosince 2012, originally named StormDB
Current release1.0.6735, June 202310 R1, October 2018
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC
Server operating systemshostedAll OS with a Java VMLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
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.yesnoyes infoXML type, but no XML query functionality
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
Clojure
Java
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoTransaction Functionsuser defined functions
TriggersBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peers
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 integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
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 developmentno
User concepts infoAccess controlnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksDatomicPostgres-XL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDatomicPostgres-XL
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