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DBMS > Badger vs. Milvus vs. RavenDB vs. Splice Machine

System Properties Comparison Badger vs. Milvus vs. RavenDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonMilvus  Xexclude from comparisonRavenDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A DBMS designed for efficient storage of vector data and vector similarity searchesOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeVector DBMSDocument storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­dgraph-io/­badgermilvus.ioravendb.netsplicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgermilvus.io/­docs/­overview.mdravendb.net/­docssplicemachine.com/­how-it-works
DeveloperDGraph LabsHibernating RhinosSplice Machine
Initial release2017201920102014
Current release2.4.4, May 20245.4, July 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoAGPL version 3, commercial license availableOpen Source infoAGPL 3.0, 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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageGoC++, GoC#Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoVector, Numeric and Stringnoyes
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 indexesnonoyesyes
SQL infoSupport of SQLnonoSQL-like query language (RQL)yes
APIs and other access methodsRESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGoC++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesyes infoJava
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyesyes
User concepts infoAccess controlnoRole based access control and fine grained access rightsAuthorization levels configured per client per databaseAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BadgerMilvusRavenDBSplice Machine
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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BadgerMilvusRavenDBSplice Machine
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