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DBMS > Ehcache vs. HEAVY.AI vs. Milvus vs. Quasardb

System Properties Comparison Ehcache vs. HEAVY.AI vs. Milvus vs. Quasardb

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMilvus  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsA 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 searchesDistributed, high-performance timeseries database
Primary database modelKey-value storeRelational DBMSVector DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitewww.ehcache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
milvus.ioquasar.ai
Technical documentationwww.ehcache.org/­documentationdocs.heavy.aimilvus.io/­docs/­overview.mddoc.quasar.ai/­master
DeveloperTerracotta Inc, owned by Software AGHEAVY.AI, Inc.quasardb
Initial release2009201620192009
Current release3.10.0, March 20225.10, January 20222.3.4, January 20243.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
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 languageJavaC++ and CUDAC++, GoC++
Server operating systemsAll OS with a Java VMLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
BSD
Linux
OS X
Windows
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes infointeger and binary
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 indexesnononoyes infowith tags
SQL infoSupport of SQLnoyesnoSQL-like query language
APIs and other access methodsJCacheJDBC
ODBC
Thrift
Vega
RESTful HTTP APIHTTP API
Supported programming languagesJavaAll languages supporting JDBC/ODBC/Thrift
Python
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnononono
Triggersyes infoCache Event Listenersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infoRound robinShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerMulti-source replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate 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 resourcenonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infoTransient mode
User concepts infoAccess controlnofine grained access rights according to SQL-standardRole based access control and fine grained access rightsCryptographically strong user authentication and audit trail
More information provided by the system vendor
EhcacheHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MilvusQuasardb
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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EhcacheHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MilvusQuasardb
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