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DBMS > HBase vs. Spark SQL vs. STSdb vs. TerarkDB

System Properties Comparison HBase vs. Spark SQL vs. STSdb vs. TerarkDB

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTerarkDB  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 methodA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelWide column storeRelational DBMSKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score31.25
Rank#26  Overall
#2  Wide column stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Score0.04
Rank#377  Overall
#58  Key-value stores
Websitehbase.apache.orgspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4github.com/­bytedance/­terarkdb
Technical documentationhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationSTS Soft SCByteDance, originally Terark
Initial release2008201420112016
Current release2.3.4, January 20213.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoGPLv2, commercial license availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC#C++
Server operating systemsLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Windows
Data schemeschema-free, schema definition possibleyesyesschema-free
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes infoprimitive types and user defined types (classes)no
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
Secondary indexesnononono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnono
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
.NET Client APIC++ API
Java API
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
C#
Java
C++
Java
Server-side scripts infoStored proceduresyes infoCoprocessors in Javanonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenonenone
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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)nonono
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.yesnoyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnonono

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More resources
HBaseSpark SQLSTSdbTerarkDB
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