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DBMS > Microsoft Azure Synapse Analytics vs. Milvus vs. RDF4J vs. Sphinx

System Properties Comparison Microsoft Azure Synapse Analytics vs. Milvus vs. RDF4J vs. Sphinx

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Editorial information provided by DB-Engines
NameMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSVector DBMSRDF storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteazure.microsoft.com/­services/­synapse-analyticsmilvus.iordf4j.orgsphinxsearch.com
Technical documentationdocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mdrdf4j.org/­documentationsphinxsearch.com/­docs
DeveloperMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sphinx Technologies Inc.
Initial release2016201920042001
Current release2.3.4, January 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
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++, GoJavaC++
Server operating systemshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesno
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 indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesnonoSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Proprietary protocol
Supported programming languagesC#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresTransact SQLnoyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlyesRole based access control and fine grained access rightsnono
More information provided by the system vendor
Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusRDF4J infoformerly known as SesameSphinx
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
Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusRDF4J infoformerly known as SesameSphinx
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