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DBMS > Ehcache vs. Hawkular Metrics vs. HEAVY.AI vs. Milvus

System Properties Comparison Ehcache vs. Hawkular Metrics vs. HEAVY.AI vs. Milvus

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelKey-value storeTime Series DBMSRelational DBMSVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Websitewww.ehcache.orgwww.hawkular.orggithub.com/­heavyai/­heavydb
www.heavy.ai
milvus.io
Technical documentationwww.ehcache.org/­documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.heavy.aimilvus.io/­docs/­overview.md
DeveloperTerracotta Inc, owned by Software AGCommunity supported by Red HatHEAVY.AI, Inc.
Initial release2009201420162019
Current release3.10.0, March 20225.10, January 20222.4.4, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availableOpen 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++ and CUDAC++, Go
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
LinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesVector, 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
Secondary indexesnononono
SQL infoSupport of SQLnonoyesno
APIs and other access methodsJCacheHTTP RESTJDBC
ODBC
Thrift
Vega
RESTful HTTP API
Supported programming languagesJavaGo
Java
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononono
Triggersyes infoCache Event Listenersyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infobased on CassandraSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serverselectable replication factor infobased on CassandraMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyBounded 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 datayes infosupports JTA and can work as an XA resourcenonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
EhcacheHawkular MetricsHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Milvus
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....
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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...
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Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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EhcacheHawkular MetricsHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Milvus
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