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DBMS > Badger vs. OushuDB vs. Splice Machine vs. WakandaDB

System Properties Comparison Badger vs. OushuDB vs. Splice Machine vs. WakandaDB

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonOushuDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningOpen-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 DBMSRelational 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
Score0.04
Rank#363  Overall
#154  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitegithub.com/­dgraph-io/­badgerwww.oushu.com/­product/­oushuDBsplicemachine.comwakanda.github.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.oushu.com/­documentationsplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperDGraph LabsOushuSplice MachineWakanda SAS
Initial release201720142012
Current release4.0.1, August 20203.1, March 20212.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen 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

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Implementation languageGoJavaC++, JavaScript
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLnoFull-featured ANSI SQL supportyesno
APIs and other access methodsJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesGoC
C++
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresnoyesyes infoJavayes
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneyesShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
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 controlnoKerberos, SSL and role based accessAccess rights for users, groups and roles according to SQL-standardyes

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More resources
BadgerOushuDBSplice MachineWakandaDB
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