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DBMS > Databricks vs. Realm vs. RethinkDB vs. Spark SQL

System Properties Comparison Databricks vs. Realm vs. RethinkDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonRealm  Xexclude from comparisonRethinkDB  Xexclude from comparisonSpark SQL  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.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataDBMS for the Web with a mechanism to push updated query results to applications in realtime.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Document storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score2.66
Rank#107  Overall
#20  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comrealm.iorethinkdb.comspark.apache.org/­sql
Technical documentationdocs.databricks.comrealm.io/­docsrethinkdb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksRealm, acquired by MongoDB in May 2019The Linux Foundation infosince July 2017Apache Software Foundation
Initial release2013201420092014
Current release2.4.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemshostedAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, binary, float, bool, date, geometryyes
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.yesnonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLnonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesno inforuns within the applications so server-side scripts are unnecessaryno
Triggersyes infoChange ListenersClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding inforange basedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCC basedyes
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.noyes infoIn-Memory realmnono
User concepts infoAccess controlyesyes infousers and table-level permissionsno
More information provided by the system vendor
DatabricksRealmRethinkDBSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksRealmRethinkDBSpark SQL
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