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DBMS > Oracle Berkeley DB vs. Spark SQL vs. SWC-DB vs. Teradata Aster vs. Transbase

System Properties Comparison Oracle Berkeley DB vs. Spark SQL vs. SWC-DB vs. Teradata Aster vs. Transbase

Editorial information provided by DB-Engines
NameOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTransbase  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSPlatform for big data analytics on multistructured data sources and typesA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSWide column storeRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.68
Rank#107  Overall
#19  Key-value stores
#3  Native XML DBMS
Score22.94
Rank#34  Overall
#20  Relational DBMS
Score0.09
Rank#309  Overall
#13  Wide column stores
Score0.08
Rank#310  Overall
#139  Relational DBMS
Websitewww.oracle.com/­technetwork/­database/­database-technologies/­berkeleydb/­overview/­index.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex KashirinTeradataTransaction Software GmbH
Initial release19942014202020051987
Current release18.1.40, May 20203.2.0, October 20210.5, April 2021Transbase 8.4, September 2020
License infoCommercial or Open SourceOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL V3commercialcommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, C++ (depending on the Berkeley DB edition)ScalaC++C and C++
Server operating systemsAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
LinuxLinuxFreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or datenoyesyesyes
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.yes infoonly with the Berkeley DB XML editionnonoyes infoin Aster File Storeno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query languageyesyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
Thrift
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.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++C
C#
C++
Java
Python
R
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnononoR packagesyes
Triggersyes infoonly for the SQL APInononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDyes
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.yesnononono
User concepts infoAccess controlnonofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Oracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column DatabaseTeradata AsterTransbase
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