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DBMS > Apache Druid vs. Netezza vs. RDF4J vs. Teradata Aster

System Properties Comparison Apache Druid vs. Netezza vs. RDF4J vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataData 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.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitedruid.apache.orgwww.ibm.com/­products/­netezzardf4j.org
Technical documentationdruid.apache.org/­docs/­latest/­designrdf4j.org/­documentation
DeveloperApache Software Foundation and contributorsIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Teradata
Initial release2012200020042005
Current release29.0.1, April 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinux
OS X
Unix
Linux infoincluded in applianceLinux
OS X
Unix
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesyes infoRDF SchemasFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyesnoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
OLE DB
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
PHP
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyesyesR packages
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoIsolation support depends on the API usedACID
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.nono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard

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More resources
Apache DruidNetezza infoAlso called PureData System for Analytics by IBMRDF4J infoformerly known as SesameTeradata Aster
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