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DBMS > Spark SQL vs. Splice Machine vs. Transbase

System Properties Comparison Spark SQL vs. Splice Machine vs. Transbase

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonTransbase  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 resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitespark.apache.org/­sqlsplicemachine.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-workswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationSplice MachineTransaction Software GmbH
Initial release201420141987
Current release3.5.0 ( 2.13), September 20233.1, March 2021Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaC and C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesJava
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoyes infoJavayes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Spark SQLSplice MachineTransbase
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