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DBMS > Databricks vs. GridDB vs. RDF4J

System Properties Comparison Databricks vs. GridDB vs. RDF4J

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  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.Scalable in-memory time series database optimized for IoT and Big DataRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Relational DBMS
Time Series DBMSRDF store
Secondary database modelsKey-value store
Relational 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.databricks.comgriddb.netrdf4j.org
Technical documentationdocs.databricks.comdocs.griddb.netrdf4j.org/­documentation
DeveloperDatabricksToshiba CorporationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release201320132004
Current release5.1, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedLinuxLinux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes
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
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesPython
R
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users can be defined per databaseno
More information provided by the system vendor
DatabricksGridDBRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
DatabricksGridDBRDF4J infoformerly known as Sesame
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