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DBMS > GigaSpaces vs. MaxDB vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB

System Properties Comparison GigaSpaces vs. MaxDB vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA robust and reliable RDBMS optimized to run all major SAP solutionsWidely 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 modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational 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 modelsGraph DBMS
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.32
Rank#112  Overall
#55  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
Websitewww.gigaspaces.commaxdb.sap.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlmaxdb.sap.com/­documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGigaspaces TechnologiesSAP, acquired from Software AG (Adabas-D) in 1997Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex Kashirin
Initial release20001984199420142020
Current release15.5, September 20207.9.10.12, February 202418.1.40, May 20203.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercial infoLimited community edition freeOpen 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

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Implementation languageJava, C++, .NetC++C, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemsLinux
macOS
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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 infoXML can be used for describing objects metadatanoyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-99 for query and DML statementsyesyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
WebDAV
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languages.Net
C++
Java
Python
Scala
.Net
C#
Java
Perl
PHP
Python
.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 proceduresyesyesnonono
Triggersyes, event driven architectureyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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.yesnoyesnono
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardnono

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More resources
GigaSpacesMaxDB infoformerly named Adabas-DOracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column Database
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