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DBMS > MonetDB vs. ObjectBox vs. Splice Machine vs. WakandaDB

System Properties Comparison MonetDB vs. ObjectBox vs. Splice Machine vs. WakandaDB

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Editorial information provided by DB-Engines
NameMonetDB  Xexclude from comparisonObjectBox  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA relational database management system that stores data in columnsLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsOpen-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 modelRelational DBMSObject oriented DBMS
Vector DBMS
Relational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.72
Rank#135  Overall
#62  Relational DBMS
Score1.08
Rank#179  Overall
#6  Object oriented DBMS
#9  Vector DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.monetdb.orggithub.com/­objectbox
objectbox.io
splicemachine.comwakanda.github.io
Technical documentationwww.monetdb.org/­Documentationdocs.objectbox.iosplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperMonetDB BVObjectBox LimitedSplice MachineWakanda SAS
Initial release2004201720142012
Current releaseDec2023 (11.49), December 20234.0 (May 2024)3.1, March 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoMozilla Public License 2.0Bindings are released under Apache 2.0 infoApache License 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC and C++JavaC++, JavaScript
Server operating systemsFreeBSD
Linux
OS X
Solaris
Windows
Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes, plus "flex" map-like typesyesyes
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLyes infoSQL 2003 with some extensionsnoyesno
APIs and other access methodsJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Proprietary native APIJDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyes, in SQL, C, Rnoyes infoJavayes
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding via remote tablesnoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoSource-replica replication available in experimental statusData sync between devices allowing occasional connected databases to work completely offlineMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standardyes
More information provided by the system vendor
MonetDBObjectBoxSplice MachineWakandaDB
News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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More resources
MonetDBObjectBoxSplice MachineWakandaDB
Recent citations in the news

MonetDB Foundation launched
31 January 2024, Centrum Wiskunde & Informatica (CWI)

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

How MonetDB/X100 Exploits Modern CPU Performance
14 January 2020, Towards Data Science

Monet DB The Column-Store Pioneer
4 September 2019, Open Source For You

ServiceNow ordered a year's worth of hardware to avoid supply chain hassles
25 May 2022, The Register

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Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning
19 January 2021, PR Newswire

2021: The Year of the Feature Store
19 January 2021, Datanami

Monte Zweben's Splice Machine Introduces New Hadoop RDBMS
24 June 2014, Forbes

Hadoop is not a static data repository, says Splice Machine CEO | #BigDataSV
12 February 2014, SiliconANGLE News

provided by Google News



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