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DBMS > Milvus vs. searchxml vs. TimescaleDB

System Properties Comparison Milvus vs. searchxml vs. TimescaleDB

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Editorial information provided by DB-Engines
NameMilvus  Xexclude from comparisonsearchxml  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA DBMS designed for efficient storage of vector data and vector similarity searchesDBMS for structured and unstructured content wrapped with an application serverA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelVector DBMSNative XML DBMS
Search engine
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitemilvus.iowww.searchxml.net/­category/­productswww.timescale.com
Technical documentationmilvus.io/­docs/­overview.mdwww.searchxml.net/­support/­handoutsdocs.timescale.com
Developerinformationpartners gmbhTimescale
Initial release201920152017
Current release2.3.4, January 20241.02.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
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++, GoC++C
Server operating systemsLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
WindowsLinux
OS X
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateVector, Numeric and Stringyesnumerics, 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.noyesyes
Secondary indexesnoyesyes
SQL infoSupport of SQLnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP APIRESTful HTTP API
WebDAV
XQuery
XSLT
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC++
Go
Java
JavaScript (Node.js)
Python
C++ infomost other programming languages supported via APIs.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoon the application serveruser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infosychronisation to multiple collectionsSource-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 systemBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writerACID
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.yesnono
User concepts infoAccess controlRole based access control and fine grained access rightsDomain, group and role-based access control at the document level and for application servicesfine grained access rights according to SQL-standard
More information provided by the system vendor
MilvussearchxmlTimescaleDB
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
MilvussearchxmlTimescaleDB
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, ibm.com

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4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

provided by Google News



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