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DBMS > Apache Drill vs. Heroic vs. Linter vs. Netezza

System Properties Comparison Apache Drill vs. Heroic vs. Linter vs. Netezza

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonHeroic  Xexclude from comparisonLinter  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchRDBMS for high security requirementsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#126  Overall
#23  Document stores
#60  Relational DBMS
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score0.03
Rank#368  Overall
#156  Relational DBMS
Score7.56
Rank#48  Overall
#31  Relational DBMS
Websitedrill.apache.orggithub.com/­spotify/­heroiclinter.ruwww.ibm.com/­products/­netezza
Technical documentationdrill.apache.org/­docsspotify.github.io/­heroic
DeveloperApache Software FoundationSpotifyrelex.ruIBM
Initial release2012201419902000
Current release1.20.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++
Server operating systemsLinux
OS X
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux infoincluded in appliance
Data schemeschema-freeschema-freeyesyes
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.nonono
Secondary indexesnoyes infovia Elasticsearchyesyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnoyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
JDBC
ODBC
OLE DB
Supported programming languagesC++C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyes infoproprietary syntax with the possibility to convert from PL/SQLyes
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyes
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 sourcefine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
Apache DrillHeroicLinterNetezza infoAlso called PureData System for Analytics by IBM
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
27 September 2019, Towards Data Science

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, Business Wire

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, azure.microsoft.com

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

provided by Google News



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