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DBMS > Apache IoTDB vs. GeoSpock vs. Milvus vs. PouchDB vs. Prometheus

System Properties Comparison Apache IoTDB vs. GeoSpock vs. Milvus vs. PouchDB vs. Prometheus

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonMilvus  Xexclude from comparisonPouchDB  Xexclude from comparisonPrometheus  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
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 FlinkSpatial and temporal data processing engine for extreme data scaleA DBMS designed for efficient storage of vector data and vector similarity searchesJavaScript DBMS with an API inspired by CouchDBOpen-source Time Series DBMS and monitoring system
Primary database modelTime Series DBMSRelational DBMSVector DBMSDocument storeTime Series DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websiteiotdb.apache.orggeospock.commilvus.iopouchdb.comprometheus.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlmilvus.io/­docs/­overview.mdpouchdb.com/­guidesprometheus.io/­docs
DeveloperApache Software FoundationGeoSpockApache Software Foundation
Initial release2018201920122015
Current release1.1.0, April 20232.0, September 20192.3.4, January 20247.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
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 languageJavaJava, JavascriptC++, GoJavaScriptGo
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-less, requires a JavaScript environment (browser, Node.js)Linux
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and StringnoNumeric data only
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.nonononono infoImport of XML data possible
Secondary indexesyestemporal, categoricalnoyes infovia viewsno
SQL infoSupport of SQLSQL-like query languageANSI SQL for query only (using Presto)nonono
APIs and other access methodsJDBC
Native API
JDBCRESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyesnonoView functions in JavaScriptno
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic shardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistencynone
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesno
User concepts infoAccess controlyesAccess rights for users can be defined per tableRole based access control and fine grained access rightsnono
More information provided by the system vendor
Apache IoTDBGeoSpockMilvusPouchDBPrometheus
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 IoTDBGeoSpockMilvusPouchDBPrometheus
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