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DBMS > FatDB vs. Linter vs. Milvus vs. Splice Machine

System Properties Comparison FatDB vs. Linter vs. Milvus vs. Splice Machine

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonLinter  Xexclude from comparisonMilvus  Xexclude from comparisonSplice Machine  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.RDBMS for high security requirementsA 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 modelDocument store
Key-value store
Relational DBMSVector DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitelinter.rumilvus.iosplicemachine.com
Technical documentationmilvus.io/­docs/­overview.mdsplicemachine.com/­how-it-works
DeveloperFatCloudrelex.ruSplice Machine
Initial release2012199020192014
Current release2.3.4, January 20243.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen 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 languageC#C and C++C++, GoJava
Server operating systemsWindowsAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
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 dateyesyesVector, 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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLno infoVia inetgration in SQL Serveryesnoyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes infoproprietary syntax with the possibility to convert from PL/SQLnoyes infoJava
Triggersyes infovia applicationsyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyBounded 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 datanoACIDnoACID
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.yesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardRole 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
FatDBLinterMilvusSplice 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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FatDBLinterMilvusSplice Machine
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