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DBMS > HBase vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Transbase

System Properties Comparison HBase vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Transbase

Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelWide column storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score31.25
Rank#26  Overall
#2  Wide column stores
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#377  Overall
#58  Key-value stores
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitehbase.apache.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­bytedance/­terarkdbwww.transaction.de/­en/­products/­transbase.html
Technical documentationhbase.apache.org/­book.htmldocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationByteDance, originally TerarkTransaction Software GmbH
Initial release20081994201420161987
Current release2.3.4, January 202118.1.40, May 20203.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infocommercial license availableOpen Source infoApache 2.0commercial inforestricted open source version availablecommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)ScalaC++C and C++
Server operating systemsLinux
Unix
Windows infousing Cygwin
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-free, schema definition possibleschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROnoyesnoyes
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.noyes infoonly with the Berkeley DB XML editionnonono
Secondary indexesnoyesnonoyes
SQL infoSupport of SQLnoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsnoyes
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
C++ API
Java API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C++
Java
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoCoprocessors in Javanononoyes
Triggersyesyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)ACIDnonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnononofine grained access rights according to SQL-standard

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More resources
HBaseOracle Berkeley DBSpark SQLTerarkDBTransbase
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