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DBMS > Greenplum vs. Hazelcast vs. Kinetica vs. Milvus

System Properties Comparison Greenplum vs. Hazelcast vs. Kinetica vs. Milvus

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Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonHazelcast  Xexclude from comparisonKinetica  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A widely adopted in-memory data gridFully vectorized database across both GPUs and CPUsA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSKey-value storeRelational DBMSVector DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.23
Rank#47  Overall
#30  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Websitegreenplum.orghazelcast.comwww.kinetica.commilvus.io
Technical documentationdocs.greenplum.orghazelcast.org/­imdg/­docsdocs.kinetica.commilvus.io/­docs/­overview.md
DeveloperPivotal Software Inc.HazelcastKinetica
Initial release2005200820122019
Current release7.0.0, September 20235.3.6, November 20237.1, August 20212.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialOpen 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, C++C++, Go
Server operating systemsLinuxAll OS with a Java VMLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesschema-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.yes infosince Version 4.2yes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
Java
Perl
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesuser defined functionsno
Triggersyesyes infoEventsyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configurationBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednono
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.noyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlAccess rights for users and roles on table levelRole based access control and fine grained access rights
More information provided by the system vendor
GreenplumHazelcastKineticaMilvus
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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