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DBMS > GigaSpaces vs. MonetDB vs. Postgres-XL vs. Splice Machine vs. WakandaDB

System Properties Comparison GigaSpaces vs. MonetDB vs. Postgres-XL vs. Splice Machine vs. WakandaDB

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonMonetDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA relational database management system that stores data in columnsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsGraph DBMS
Search engine
Document store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.gigaspaces.comwww.monetdb.orgwww.postgres-xl.orgsplicemachine.comwakanda.github.io
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlwww.monetdb.org/­Documentationwww.postgres-xl.org/­documentationsplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperGigaspaces TechnologiesMonetDB BVSplice MachineWakanda SAS
Initial release200020042014 infosince 2012, originally named StormDB20142012
Current release15.5, September 2020Dec2023 (11.49), December 202310 R1, October 20183.1, March 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoMozilla Public License 2.0Open Source infoMozilla public licenseOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPLv3, extended 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 languageJava, C++, .NetCCJavaC++, JavaScript
Server operating systemsLinux
macOS
Solaris
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 metadatayes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsyes infoSQL 2003 with some extensionsyes infodistributed, parallel query executionyesno
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languages.Net
C++
Java
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyesyes, in SQL, C, Ruser defined functionsyes infoJavayes
Triggersyes, event driven architectureyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding via remote tableshorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
none infoSource-replica replication available in experimental statusMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoMVCCACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
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.yesnoyesno
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardyes

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More resources
GigaSpacesMonetDBPostgres-XLSplice MachineWakandaDB
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