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DBMS > HBase vs. Spark SQL vs. STSdb vs. Valentina Server

System Properties Comparison HBase vs. Spark SQL vs. STSdb vs. Valentina Server

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodObject-relational database and reports server
Primary database modelWide column storeRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score30.50
Rank#26  Overall
#2  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitehbase.apache.orgspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.valentina-db.net
Technical documentationhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationSTS Soft SCParadigma Software
Initial release2008201420111999
Current release2.3.4, January 20213.5.0 ( 2.13), September 20234.0.8, September 20155.7.5
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache 2.0Open 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 languageJavaScalaC#
Server operating systemsLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
WindowsLinux
OS X
Windows
Data schemeschema-free, schema definition possibleyesyesyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes 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 SQLnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
.NET Client APIODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
C#
Java
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infoCoprocessors in Javanonoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnoyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnonofine grained access rights according to SQL-standard

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More resources
HBaseSpark SQLSTSdbValentina Server
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