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DBMS > Databricks vs. Milvus vs. RDF4J vs. Yanza

System Properties Comparison Databricks vs. Milvus vs. RDF4J vs. Yanza

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMilvus  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.A DBMS designed for efficient storage of vector data and vector similarity searchesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Time Series DBMS for IoT Applications
Primary database modelDocument store
Relational DBMS
Vector DBMSRDF storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.databricks.commilvus.iordf4j.orgyanza.com
Technical documentationdocs.databricks.commilvus.io/­docs/­overview.mdrdf4j.org/­documentation
DeveloperDatabricksSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Yanza
Initial release2013201920042015
Current release2.3.4, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoEclipse Distribution License (EDL), v1.0.commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnonono infobut mainly used as a service provided by Yanza
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 languageC++, GoJava
Server operating systemshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Unix
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateVector, Numeric and Stringyesno
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.yesnono
Secondary indexesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLnonono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
HTTP API
Supported programming languagesPython
R
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Java
PHP
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyesno
Triggersnoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlRole based access control and fine grained access rightsnono
More information provided by the system vendor
DatabricksMilvusRDF4J infoformerly known as SesameYanza
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Milvus is an open-source and cloud-native vector database built for production-ready...
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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,...
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Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
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Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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DatabricksMilvusRDF4J infoformerly known as SesameYanza
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