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DBMS > Badger vs. Drizzle vs. InterSystems IRIS vs. Splice Machine vs. WakandaDB

System Properties Comparison Badger vs. Drizzle vs. InterSystems IRIS vs. Splice Machine vs. WakandaDB

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDrizzle  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityOpen-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 modelKey-value storeRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitegithub.com/­dgraph-io/­badgerwww.intersystems.com/­products/­intersystems-irissplicemachine.comwakanda.github.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clssplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperDGraph LabsDrizzle project, originally started by Brian AkerInterSystemsSplice MachineWakanda SAS
Initial release20172008201820142012
Current release7.2.4, September 20122023.3, June 20233.1, March 20212.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGNU GPLcommercialOpen 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 languageGoC++JavaC++, JavaScript
Server operating systemsBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
AIX
Linux
macOS
Ubuntu
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesdepending on used data modelyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.noyesno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsyesyesno
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesGoC
C++
Java
PHP
.Net
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresnonoyesyes infoJavayes
Triggersnono infohooks for callbacks inside the server can be used.yesyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID
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.noyesyesno
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPyesAccess rights for users, groups and roles according to SQL-standardyes
More information provided by the system vendor
BadgerDrizzleInterSystems IRISSplice MachineWakandaDB
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
BadgerDrizzleInterSystems IRISSplice MachineWakandaDB
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