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DBMS > DataFS vs. RethinkDB vs. Rockset vs. Spark SQL

System Properties Comparison DataFS vs. RethinkDB vs. Rockset vs. Spark SQL

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonRethinkDB  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.DBMS for the Web with a mechanism to push updated query results to applications in realtime.A scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSDocument storeDocument storeRelational DBMS
Secondary database modelsGraph DBMSSpatial DBMSRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitenewdatabase.comrethinkdb.comrockset.comspark.apache.org/­sql
Technical documentationdev.mobiland.com/­Overview.xsprethinkdb.com/­docsdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMobiland AGThe Linux Foundation infosince July 2017RocksetApache Software Foundation
Initial release2018200920192014
Current release1.1.263, October 20222.4.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Scala
Server operating systemsWindowsLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, binary, float, bool, date, geometrydynamic typingyes
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.nonono infoingestion from XML files supportedno
Secondary indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLnonoRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
HTTP RESTJDBC
ODBC
Supported programming languages.Net
C
C#
C++
VB.Net
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
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersno, except callback-events from server when changes happenedClient-side triggers through changefeedsnono
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemSharding inforange basedAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-document operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCC basedyesyes
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 controlWindows-Profileyes infousers and table-level permissionsAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
DataFSRethinkDBRocksetSpark SQL
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