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DBMS > Databricks vs. Netezza vs. RDF4J

System Properties Comparison Databricks vs. Netezza vs. RDF4J

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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.Data warehouse and analytics appliance part of IBM PureSystemsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Relational DBMS
Relational DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.databricks.comwww.ibm.com/­products/­netezzardf4j.org
Technical documentationdocs.databricks.comrdf4j.org/­documentation
DeveloperDatabricksIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release201320002004
License infoCommercial or Open SourcecommercialcommercialOpen 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 languageJava
Server operating systemshostedLinux infoincluded in applianceLinux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes
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
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
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++
Fortran
Java
Lua
Perl
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyes
Triggersnoyes
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 methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID 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.no
User concepts infoAccess controlUsers with fine-grained authorization conceptno
More information provided by the system vendor
DatabricksNetezza infoAlso called PureData System for Analytics by IBMRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksNetezza infoAlso called PureData System for Analytics by IBMRDF4J infoformerly known as Sesame
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