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DBMS > Apache Pinot vs. Microsoft SQL Server vs. Milvus vs. TimescaleDB

System Properties Comparison Apache Pinot vs. Microsoft SQL Server vs. Milvus vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonMilvus  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyMicrosofts flagship relational DBMSA DBMS designed for efficient storage of vector data and vector similarity searchesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSVector DBMSTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#274  Overall
#128  Relational DBMS
Score807.76
Rank#3  Overall
#3  Relational DBMS
Score3.01
Rank#89  Overall
#4  Vector DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitepinot.apache.orgwww.microsoft.com/­en-us/­sql-servermilvus.iowww.timescale.com
Technical documentationdocs.pinot.apache.orglearn.microsoft.com/­en-US/­sql/­sql-servermilvus.io/­docs/­overview.mddocs.timescale.com
DeveloperApache Software Foundation and contributorsMicrosoftTimescale
Initial release2015198920192017
Current release1.0.0, September 2023SQL Server 2022, November 20222.4.4, May 20242.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial inforestricted free version is availableOpen Source infoApache Version 2.0Open Source infoApache 2.0
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.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJavaC++C++, GoC
Server operating systemsAll OS with a Java JDK11 or higherLinux
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnoyes
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query languageyesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javanouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningtables can be distributed across several files (horizontal partitioning); sharding through federationShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, but depending on the SQL-Server EditionSource-replica replication with hot standby and reads on replicas info
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
Immediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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 rightsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache PinotMicrosoft SQL ServerMilvusTimescaleDB
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
Apache PinotMicrosoft SQL ServerMilvusTimescaleDB
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Conferences, events and webinars

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

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