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DBMS > Databricks vs. Geode vs. Netezza vs. RDF4J

System Properties Comparison Databricks vs. Geode vs. Netezza vs. RDF4J

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeode  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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesData 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
Key-value storeRelational DBMSRDF store
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
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.databricks.comgeode.apache.orgwww.ibm.com/­products/­netezzardf4j.org
Technical documentationdocs.databricks.comgeode.apache.org/­docsrdf4j.org/­documentation
DeveloperDatabricksOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.IBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2013200220002004
Current release1.1, February 2017
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux infoincluded in applianceLinux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (OQL)yesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java Client API
Memcached protocol
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
.Net
All JVM based languages
C++
Groovy
Java
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyesyes
Triggersyes infoCache Event Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 per client and object definableUsers with fine-grained authorization conceptno
More information provided by the system vendor
DatabricksGeodeNetezza 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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DatabricksGeodeNetezza infoAlso called PureData System for Analytics by IBMRDF4J infoformerly known as Sesame
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