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DBMS > atoti vs. jBASE vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB

System Properties Comparison atoti vs. jBASE vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonjBASE  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A robust multi-value DBMS comprising development tools and middlewareWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelObject oriented DBMSMultivalue DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiteatoti.iowww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.atoti.iodocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamRocket Software (formerly Zumasys)Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex Kashirin
Initial release1991199420142020
Current release5.718.1.40, May 20203.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL V3
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++
Server operating systemsAIX
Linux
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateoptionalnoyes
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.yesyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)Embedded SQL for jBASE in BASICyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languages.Net
Basic
Jabbascript
Java
.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++
Server-side scripts infoStored proceduresPythonyesnonono
Triggersyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingnoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
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.yesyesyesnono
User concepts infoAccess controlAccess rights can be defined down to the item levelnono

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More resources
atotijBASEOracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column Database
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