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DBMS > Apache Phoenix vs. GreptimeDB vs. Milvus vs. Yanza

System Properties Comparison Apache Phoenix vs. GreptimeDB vs. Milvus vs. Yanza

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGreptimeDB  Xexclude from comparisonMilvus  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAn open source Time Series DBMS built for increased scalability, high performance and efficiencyA DBMS designed for efficient storage of vector data and vector similarity searchesTime Series DBMS for IoT Applications
Primary database modelRelational DBMSTime Series DBMSVector DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.06
Rank#352  Overall
#33  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitephoenix.apache.orggreptime.commilvus.ioyanza.com
Technical documentationphoenix.apache.orgdocs.greptime.commilvus.io/­docs/­overview.md
DeveloperApache Software FoundationGreptime Inc.Yanza
Initial release2014202220192015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
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 languageJavaRustC++, Go
Server operating systemsLinux
Unix
Windows
Android
Docker
FreeBSD
Linux
macOS
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringno
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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesyesnono
APIs and other access methodsJDBCgRPC
HTTP API
JDBC
RESTful HTTP APIHTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C++
Erlang
Go
Java
JavaScript
C++
Go
Java
JavaScript (Node.js)
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsPythonnono
Triggersnonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancySimple rights management via user accountsRole based access control and fine grained access rightsno
More information provided by the system vendor
Apache PhoenixGreptimeDBMilvusYanza
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Milvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Highly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
As of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more
Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
Apache PhoenixGreptimeDBMilvusYanza
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, Microsoft

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

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26 March 2024, The New Stack

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31 January 2024, SitePoint

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

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

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

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