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DBMS > HBase vs. Spark SQL vs. SWC-DB vs. TerarkDB

System Properties Comparison HBase vs. Spark SQL vs. SWC-DB vs. TerarkDB

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 processingA high performance, scalable Wide Column DBMSA 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 DBMSWide column storeKey-value store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score27.97
Rank#26  Overall
#2  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Score0.08
Rank#367  Overall
#56  Key-value stores
Websitehbase.apache.orgspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
github.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 FoundationAlex KashirinByteDance, originally Terark
Initial release2008201420202016
Current release2.3.4, January 20213.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoGPL V3commercial 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
Linux
Data schemeschema-free, schema definition possibleyesschema-freeschema-free
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesno
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.nononono
Secondary indexesnonono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageno
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Proprietary protocol
Thrift
C++ API
Java API
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
C++C++
Java
Server-side scripts infoStored proceduresyes infoCoprocessors in Javanonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShardingnone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
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 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.yesnonoyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono

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More resources
HBaseSpark SQLSWC-DB infoSuper Wide Column DatabaseTerarkDB
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