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DBMS > Linter vs. Milvus vs. PlanetScale vs. Spark SQL

System Properties Comparison Linter vs. Milvus vs. PlanetScale vs. Spark SQL

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Editorial information provided by DB-Engines
NameLinter  Xexclude from comparisonMilvus  Xexclude from comparisonPlanetScale  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionRDBMS for high security requirementsA DBMS designed for efficient storage of vector data and vector similarity searchesScalable, distributed, serverless MySQL database platform built on top of VitessSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSVector DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial 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
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitelinter.rumilvus.ioplanetscale.comspark.apache.org/­sql
Technical documentationmilvus.io/­docs/­overview.mdplanetscale.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developerrelex.ruPlanetScaleApache Software Foundation
Initial release1990201920202014
Current release2.3.4, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
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 and C++C++, GoGoScala
Server operating systemsAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Docker
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLyesnoyes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C++
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoproprietary syntax with the possibility to convert from PL/SQLnoyes infoproprietary syntaxno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at shard levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole based access control and fine grained access rightsUsers with fine-grained authorization concept infono user groups or rolesno
More information provided by the system vendor
LinterMilvusPlanetScaleSpark SQL
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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More resources
LinterMilvusPlanetScaleSpark SQL
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