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DBMS > Drizzle vs. Hawkular Metrics vs. Milvus vs. TimescaleDB

System Properties Comparison Drizzle vs. Hawkular Metrics vs. Milvus vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMilvus  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Hawkular 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 searchesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMSVector DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.hawkular.orgmilvus.iowww.timescale.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemilvus.io/­docs/­overview.mddocs.timescale.com
DeveloperDrizzle project, originally started by Brian AkerCommunity supported by Red HatTimescale
Initial release2008201420192017
Current release7.2.4, September 20122.3.4, January 20242.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 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 languageC++JavaC++, GoC
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringnumerics, 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.nonoyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCHTTP RESTRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Java
PHP
Go
Java
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnononouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
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
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.noyesno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoRole based access control and fine grained access rightsfine grained access rights according to SQL-standard
More information provided by the system vendor
DrizzleHawkular MetricsMilvusTimescaleDB
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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DrizzleHawkular MetricsMilvusTimescaleDB
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