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DBMS > Spark SQL vs. Splice Machine vs. SQream DB vs. TinkerGraph

System Properties Comparison Spark SQL vs. Splice Machine vs. SQream DB vs. TinkerGraph

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Sparka GPU-based, columnar RDBMS for big data analytics workloadsA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelRelational DBMSRelational DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websitespark.apache.org/­sqlsplicemachine.comsqream.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperApache Software FoundationSplice MachineSQream Technologies
Initial release2014201420172009
Current release3.5.0 ( 2.13), September 20233.1, March 20212022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaC++, CUDA, Haskell, Java, ScalaJava
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes
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.nono
Secondary indexesnoyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesno
APIs and other access methodsJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
TinkerPop 3
Supported programming languagesJava
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Groovy
Java
Server-side scripts infoStored proceduresnoyes infoJavauser defined functions in Pythonno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal and vertical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynoyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesno
Durability infoSupport for making data persistentyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
Spark SQLSplice MachineSQream DBTinkerGraph
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