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DBMS > Databricks vs. Geode vs. Hazelcast vs. Milvus

System Properties Comparison Databricks vs. Geode vs. Hazelcast vs. Milvus

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeode  Xexclude from comparisonHazelcast  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA widely adopted in-memory data gridA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument store
Relational DBMS
Key-value storeKey-value storeVector DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score2.78
Rank#103  Overall
#3  Vector DBMS
Websitewww.databricks.comgeode.apache.orghazelcast.commilvus.io
Technical documentationdocs.databricks.comgeode.apache.org/­docshazelcast.org/­imdg/­docsmilvus.io/­docs/­overview.md
DeveloperDatabricksOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Hazelcast
Initial release2013200220082019
Current release1.1, February 20175.3.6, November 20232.3.4, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
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++, Go
Server operating systemshostedAll OS with a Java VM infothe JDK (8 or later) is also requiredAll OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-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.yesnoyes infothe object must implement a serialization strategyno
Secondary indexesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (OQL)SQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyes infoEvent Listeners, Executor Servicesno
Triggersyes infoCache Event Listenersyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeone or two-phase-commit; repeatable reads; read commitedno
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.noyesyesyes
User concepts infoAccess controlAccess rights per client and object definableRole-based access controlRole based access control and fine grained access rights
More information provided by the system vendor
DatabricksGeodeHazelcastMilvus
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Milvus 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,...
» 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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