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

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

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonSplice Machine  Xexclude from comparisonSurrealDB  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA fully ACID transactional, developer-friendly, multi-model DBMSWakandaDB 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
Graph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitegithub.com/­dgraph-io/­badgersplicemachine.comsurrealdb.comwakanda.github.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgersplicemachine.com/­how-it-workssurrealdb.com/­docswakanda.github.io/­doc
DeveloperDGraph LabsSplice MachineSurrealDB LtdWakanda SAS
Initial release2017201420222012
Current release3.1, March 2021v1.1.1, January 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen SourceOpen 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 languageGoJavaRustC++, JavaScript
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
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 indexesnoyes
SQL infoSupport of SQLnoyesSQL-like query languageno
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
GraphQL
RESTful HTTP API
WebSocket
RESTful HTTP API
Supported programming languagesGoC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
JavaScript
Server-side scripts infoStored proceduresnoyes infoJavayes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShared 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 methodsnoYes, via Full Spark Integrationnono
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 datayesyes, multi-version concurrency control (MVCC)yesyes
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 controlnoAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rulesyes

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More resources
BadgerSplice MachineSurrealDBWakandaDB
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