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DBMS > Hazelcast vs. HEAVY.AI vs. LMDB vs. Milvus

System Properties Comparison Hazelcast vs. HEAVY.AI vs. LMDB vs. Milvus

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLMDB  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionA widely adopted in-memory data gridA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA high performant, light-weight, embedded key-value database libraryA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelKey-value storeRelational DBMSKey-value storeVector DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitehazelcast.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.symas.com/­symas-embedded-database-lmdbmilvus.io
Technical documentationhazelcast.org/­imdg/­docsdocs.heavy.aiwww.lmdb.tech/­docmilvus.io/­docs/­overview.md
DeveloperHazelcastHEAVY.AI, Inc.Symas
Initial release2008201620112019
Current release5.3.6, November 20235.10, January 20220.9.32, January 20242.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2; enterprise edition availableOpen SourceOpen 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 languageJavaC++ and CUDACC++, Go
Server operating systemsAll OS with a Java VMLinuxLinux
Unix
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesVector, 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.yes infothe object must implement a serialization strategynonono
Secondary indexesyesnonono
SQL infoSupport of SQLSQL-like query languageyesnono
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
RESTful HTTP API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnonono
Triggersyes infoEventsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate 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 dataone or two-phase-commit; repeatable reads; read commitednoACIDno
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.yesyesyesyes
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardnoRole based access control and fine grained access rights
More information provided by the system vendor
HazelcastHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LMDBMilvus
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
HazelcastHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LMDBMilvus
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