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DBMS > Databricks vs. RDF4J vs. Rockset

System Properties Comparison Databricks vs. RDF4J vs. Rockset

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRockset  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.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelDocument store
Relational DBMS
RDF storeDocument store
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.82
Rank#212  Overall
#36  Document stores
Websitewww.databricks.comrdf4j.orgrockset.com
Technical documentationdocs.databricks.comrdf4j.org/­documentationdocs.rockset.com
DeveloperDatabricksSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Rockset
Initial release201320042019
License infoCommercial or Open SourcecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedLinux
OS X
Unix
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesdynamic typing
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.yesno infoingestion from XML files supported
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoRead-only SQL queries, including JOINs
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
HTTP REST
Supported programming languagesPython
R
Scala
Java
PHP
Python
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes 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.no
User concepts infoAccess controlnoAccess rights for users and organizations can be defined via Rockset console
More information provided by the system vendor
DatabricksRDF4J infoformerly known as SesameRockset
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksRDF4J infoformerly known as SesameRockset
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