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DBMS > Apache Phoenix vs. Databricks vs. Milvus vs. PouchDB vs. Prometheus

System Properties Comparison Apache Phoenix vs. Databricks vs. Milvus vs. PouchDB vs. Prometheus

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonMilvus  Xexclude from comparisonPouchDB  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A 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 modelRelational DBMSDocument store
Relational DBMS
Vector DBMSDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational 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
Websitephoenix.apache.orgwww.databricks.commilvus.iopouchdb.comprometheus.io
Technical documentationphoenix.apache.orgdocs.databricks.commilvus.io/­docs/­overview.mdpouchdb.com/­guidesprometheus.io/­docs
DeveloperApache Software FoundationDatabricksApache Software Foundation
Initial release20142013201920122015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 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 languageJavaC++, GoJavaScriptGo
Server operating systemsLinux
Unix
Windows
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-less, requires a JavaScript environment (browser, Node.js)Linux
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesVector, 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.noyesnonono infoImport of XML data possible
Secondary indexesyesyesnoyes infovia viewsno
SQL infoSupport of SQLyeswith Databricks SQLnonono
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesnoView functions in JavaScriptno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesMulti-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 methodsHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistencynone
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
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 controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyRole based access control and fine grained access rightsnono
More information provided by the system vendor
Apache PhoenixDatabricksMilvusPouchDBPrometheus
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Milvus 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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Apache PhoenixDatabricksMilvusPouchDBPrometheus
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