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DBMS > Apache Phoenix vs. Hawkular Metrics vs. Manticore Search vs. Milvus

System Properties Comparison Apache Phoenix vs. Hawkular Metrics vs. Manticore Search vs. Milvus

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonManticore Search  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Multi-storage database for search, including full-text search.A DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSTime Series DBMSSearch engineVector DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.23
Rank#301  Overall
#21  Search engines
Score3.01
Rank#89  Overall
#4  Vector DBMS
Websitephoenix.apache.orgwww.hawkular.orgmanticoresearch.commilvus.io
Technical documentationphoenix.apache.orgwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemanual.manticoresearch.commilvus.io/­docs/­overview.md
DeveloperApache Software FoundationCommunity supported by Red HatManticore Software
Initial release2014201420172019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20196.0, February 20232.4.4, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPL version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
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 languageJavaJavaC++C++, Go
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeFixed schema
Typing infopredefined data types such as float or dateyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, BooleanVector, Numeric and String
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.nonoCan index from XMLno
Secondary indexesyesnoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLyesnoSQL-like query languageno
APIs and other access methodsJDBCHTTP RESTBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnouser defined functionsno
Triggersnoyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynonoRole based access control and fine grained access rights
More information provided by the system vendor
Apache PhoenixHawkular MetricsManticore SearchMilvus
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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Apache PhoenixHawkular MetricsManticore SearchMilvus
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