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DBMS > Hawkular Metrics vs. Milvus vs. OrigoDB vs. Qdrant vs. TimescaleDB

System Properties Comparison Hawkular Metrics vs. Milvus vs. OrigoDB vs. Qdrant vs. TimescaleDB

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonMilvus  Xexclude from comparisonOrigoDB  Xexclude from comparisonQdrant  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 searchesA fully ACID in-memory object graph databaseA high-performance vector database with neural network or semantic-based matchingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSVector DBMSDocument store
Object oriented DBMS
Vector DBMSTime Series DBMS
Secondary database modelsRelational 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
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.hawkular.orgmilvus.ioorigodb.comgithub.com/­qdrant/­qdrant
qdrant.tech
www.timescale.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemilvus.io/­docs/­overview.mdorigodb.com/­docsqdrant.tech/­documentationdocs.timescale.com
DeveloperCommunity supported by Red HatRobert Friberg et alQdrantTimescale
Initial release201420192009 infounder the name LiveDB20212017
Current release2.3.4, January 20242.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
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++, GoC#RustC
Server operating systemsLinux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
Windows
Docker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesVector, Numeric and StringUser defined using .NET types and collectionsNumbers, Strings, Geo, Booleannumerics, 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.nonono infocan be achieved using .NETnoyes
Secondary indexesnonoyesyes infoKeywords, numberic ranges, geo, full-textyes
SQL infoSupport of SQLnonononoyes infofull PostgreSQL SQL syntax
APIs and other access methodsHTTP RESTRESTful HTTP API.NET Client API
HTTP API
LINQ
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
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
.Net.Net
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyesuser 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 Alertingnoyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardinghorizontal partitioning infoclient side managed; servers are not synchronizedShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationCollection-level replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
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, tunable consistencyImmediate Consistency
Foreign keys infoReferential integritynonodepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyesyes
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 rightsRole based authorizationKey-based authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
Hawkular MetricsMilvusOrigoDBQdrantTimescaleDB
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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More resources
Hawkular MetricsMilvusOrigoDBQdrantTimescaleDB
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