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DBMS > Hazelcast vs. Milvus vs. Spark SQL vs. STSdb

System Properties Comparison Hazelcast vs. Milvus vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionA widely adopted in-memory data gridA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value storeVector DBMSRelational DBMSKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitehazelcast.commilvus.iospark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationhazelcast.org/­imdg/­docsmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHazelcastApache Software FoundationSTS Soft SC
Initial release2008201920142011
Current release5.3.6, November 20232.3.4, January 20243.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJavaC++, GoScalaC#
Server operating systemsAll OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyes infoprimitive types and user defined types (classes)
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 strategynono
Secondary indexesyesnonono
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
.NET Client API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnonono
Triggersyes infoEventsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmBounded 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 commitednonono
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.yesyesno
User concepts infoAccess controlRole-based access controlRole based access control and fine grained access rightsnono
More information provided by the system vendor
HazelcastMilvusSpark SQLSTSdb
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....
» 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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HazelcastMilvusSpark SQLSTSdb
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