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

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

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFeatureBase  Xexclude from comparisonMilvus  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.A DBMS designed for efficient storage of vector data and vector similarity searchesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.featurebase.commilvus.iosplicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.featurebase.commilvus.io/­docs/­overview.mdsplicemachine.com/­how-it-works
DeveloperDGraph LabsMolecula and Pilosa Open Source ContributorsSplice Machine
Initial release2017201720192014
Current release2022, May 20222.4.4, May 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0Open 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 languageGoGoC++, GoJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesVector, Numeric and Stringyes
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.nonono
Secondary indexesnononoyes
SQL infoSupport of SQLnoSQL queriesnoyes
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesGoJava
Python
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlnoRole based access control and fine grained access rightsAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BadgerFeatureBaseMilvusSplice 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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BadgerFeatureBaseMilvusSplice Machine
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