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DBMS > Hawkular Metrics vs. Heroic vs. Hyprcubd vs. Ingres vs. Milvus

System Properties Comparison Hawkular Metrics vs. Heroic vs. Hyprcubd vs. Ingres vs. Milvus

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonHeroic  Xexclude from comparisonHyprcubd  Xexclude from comparisonIngres  Xexclude from comparisonMilvus  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchServerless Time Series DBMSWell established RDBMSA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelTime Series DBMSTime Series DBMSTime Series DBMSRelational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitewww.hawkular.orggithub.com/­spotify/­heroichyprcubd.com (offline)www.actian.com/­databases/­ingresmilvus.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidespotify.github.io/­heroicdocs.actian.com/­ingresmilvus.io/­docs/­overview.md
DeveloperCommunity supported by Red HatSpotifyHyprcubd, Inc.Actian Corporation
Initial release201420141974 infooriginally developed at University Berkely in early 1970s2019
Current release11.2, May 20222.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0commercialcommercialOpen Source infoApache Version 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 languageJavaJavaGoCC++, Go
Server operating systemsLinux
OS X
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infotime, int, uint, float, stringyesVector, 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.nononono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesnoyes infovia Elasticsearchnoyesno
SQL infoSupport of SQLnonoSQL-like query languageyesno
APIs and other access methodsHTTP RESTHQL (Heroic Query Language, a JSON-based language)
HTTP API
gRPC (https).NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
RESTful HTTP API
Supported programming languagesGo
Java
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononoyesno
Triggersyes infovia Hawkular Alertingnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandrayesIngres Replicator
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
Eventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes infoMVCCyes
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.nonononoyes
User concepts infoAccess controlnotoken accessfine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
Hawkular MetricsHeroicHyprcubdIngresMilvus
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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Hawkular MetricsHeroicHyprcubdIngresMilvus
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