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DBMS > Apache Drill vs. RDF4J vs. Trafodion

System Properties Comparison Apache Drill vs. RDF4J vs. Trafodion

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Transactional SQL-on-Hadoop DBMS
Primary database modelDocument store
Relational DBMS
RDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.28
Rank#119  Overall
#23  Document stores
#56  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Websitedrill.apache.orgrdf4j.orgtrafodion.apache.org
Technical documentationdrill.apache.org/­docsrdf4j.org/­documentationtrafodion.apache.org/­documentation.html
DeveloperApache Software FoundationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation, originally developed by HP
Initial release201220042014
Current release1.20.3, January 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java
Server operating systemsLinux
OS X
Windows
Linux
OS X
Unix
Windows
Linux
Data schemeschema-freeyes infoRDF Schemasyes
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.nono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnoyes
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
ADO.NET
JDBC
ODBC
Supported programming languagesC++Java
PHP
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functionsyesJava Stored Procedures
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyes 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.Depending on the underlying data sourceno
User concepts infoAccess controlDepending on the underlying data sourcenofine grained access rights according to SQL-standard

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More resources
Apache DrillRDF4J infoformerly known as SesameTrafodion
Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
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Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

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HP Throws Trafodion Hat into OLTP Hadoop Ring
14 July 2014, Datanami

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News



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