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DBMS > Spark SQL vs. SQream DB vs. STSdb vs. Yaacomo

System Properties Comparison Spark SQL vs. SQream DB vs. STSdb vs. Yaacomo

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonSTSdb  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitespark.apache.org/­sqlsqream.comgithub.com/­STSSoft/­STSdb4yaacomo.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperApache Software FoundationSQream TechnologiesSTS Soft SCQ2WEB GmbH
Initial release2014201720112009
Current release3.5.0 ( 2.13), September 20232022.1.6, December 20224.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPLv2, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++, CUDA, Haskell, Java, ScalaC#
Server operating systemsLinux
OS X
Windows
LinuxWindowsAndroid
Linux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes infoprimitive types and user defined types (classes)yes
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 indexesnononoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes
APIs and other access methodsJDBC
ODBC
.Net
JDBC
ODBC
.NET Client APIJDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C#
Java
Server-side scripts infoStored proceduresnouser defined functions in Pythonno
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corehorizontal and vertical partitioningnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
Spark SQLSQream DBSTSdbYaacomo
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