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DBMS > Hawkular Metrics vs. Milvus vs. PlanetScale vs. Solr vs. TimescaleDB

System Properties Comparison Hawkular Metrics vs. Milvus vs. PlanetScale vs. Solr vs. TimescaleDB

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonMilvus  Xexclude from comparisonPlanetScale  Xexclude from comparisonSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A DBMS designed for efficient storage of vector data and vector similarity searchesScalable, distributed, serverless MySQL database platform built on top of VitessA widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSVector DBMSRelational DBMSSearch engineTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.hawkular.orgmilvus.ioplanetscale.comsolr.apache.orgwww.timescale.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemilvus.io/­docs/­overview.mdplanetscale.com/­docssolr.apache.org/­resources.htmldocs.timescale.com
DeveloperCommunity supported by Red HatPlanetScaleApache Software FoundationTimescale
Initial release20142019202020062017
Current release2.3.4, January 20249.6.0, April 20242.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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++, GoGoJavaC
Server operating systemsLinux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Docker
Linux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyes infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyesyes
Secondary indexesnonoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnonoyes infowith proprietary extensionsSolr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntax
APIs and other access methodsHTTP RESTRESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes infoproprietary syntaxJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infovia Hawkular Alertingnoyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
yesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage enginenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at shard leveloptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyesno
User concepts infoAccess controlnoRole based access control and fine grained access rightsUsers with fine-grained authorization concept infono user groups or rolesyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Hawkular MetricsMilvusPlanetScaleSolrTimescaleDB
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...
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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,...
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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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Hawkular MetricsMilvusPlanetScaleSolrTimescaleDB
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