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DBMS > Apache IoTDB vs. Milvus vs. MonetDB vs. PostgreSQL vs. Sphinx

System Properties Comparison Apache IoTDB vs. Milvus vs. MonetDB vs. PostgreSQL vs. Sphinx

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMilvus  Xexclude from comparisonMonetDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA DBMS designed for efficient storage of vector data and vector similarity searchesA relational database management system that stores data in columnsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSVector DBMSRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Search engine
Secondary database modelsDocument store
Spatial DBMS
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgmilvus.iowww.monetdb.orgwww.postgresql.orgsphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlmilvus.io/­docs/­overview.mdwww.monetdb.org/­Documentationwww.postgresql.org/­docssphinxsearch.com/­docs
DeveloperApache Software FoundationMonetDB BVPostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.
Initial release2018201920041989 info1989: Postgres, 1996: PostgreSQL2001
Current release1.1.0, April 20232.3.4, January 2024Dec2023 (11.49), December 202316.3, May 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoMozilla Public License 2.0Open Source infoBSDOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, GoCCC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
FreeBSD
Linux
OS X
Solaris
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyesno
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.nonoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoyes infoSQL 2003 with some extensionsyes infostandard with numerous extensionsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesnoyes, in SQL, C, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyesnoyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding via remote tablespartitioning by range, list and (since PostgreSQL 11) by hashSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoSource-replica replication available in experimental statusSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesyesno
User concepts infoAccess controlyesRole based access control and fine grained access rightsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno
More information provided by the system vendor
Apache IoTDBMilvusMonetDBPostgreSQLSphinx
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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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...
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