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DBMS > Interbase vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB vs. YDB

System Properties Comparison Interbase vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB vs. YDB

Editorial information provided by DB-Engines
NameInterbase  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionLight-weight proven RDBMS infooriginally from BorlandWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSWide column storeDocument store
Relational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.61
Rank#72  Overall
#39  Relational 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
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitewww.embarcadero.com/­products/­interbasewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
github.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdocs.embarcadero.com/­products/­interbasedocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperEmbarcaderoOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex KashirinYandex
Initial release19841994201420202019
Current releaseInterBase 2020, December 201918.1.40, May 20203.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL V3Open Source infoApache 2.0; commercial license available
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 languageCC, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemsAndroid
iOS
Linux
OS X
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
LinuxLinux
Data schemeyesschema-freeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesnoyesyes
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.no infoexport as XML data possibleyes infoonly with the Berkeley DB XML editionnonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (YQL)
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
Thrift
RESTful HTTP API (DynamoDB compatible)
Supported programming languages.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.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++Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyes infoInterbase procedure and trigger languagenononono
Triggersyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes, utilizing Spark CoreShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInterbase Change ViewsSource-replica replicationnoneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoMultiversion concurreny controlyesyesyes
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.yesyesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoAccess rights defined for Yandex Cloud users

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More resources
InterbaseOracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column DatabaseYDB
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