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DBMS > Apache Drill vs. Apache Impala vs. Apache Pinot vs. Netezza

System Properties Comparison Apache Drill vs. Apache Impala vs. Apache Pinot vs. Netezza

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonApache Impala  Xexclude from comparisonApache Pinot  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageAnalytic DBMS for HadoopRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitedrill.apache.orgimpala.apache.orgpinot.apache.orgwww.ibm.com/­products/­netezza
Technical documentationdrill.apache.org/­docsimpala.apache.org/­impala-docs.htmldocs.pinot.apache.org
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation and contributorsIBM
Initial release2012201320152000
Current release1.20.3, January 20234.1.0, June 20221.0.0, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemsLinux
OS X
Windows
LinuxAll OS with a Java JDK11 or higherLinux infoincluded in appliance
Data schemeschema-freeyesyesyes
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.nono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBCJDBC
ODBC
OLE DB
Supported programming languagesC++All languages supporting JDBC/ODBCGo
Java
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reduceyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyes
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 sourceAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept

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More resources
Apache DrillApache ImpalaApache PinotNetezza 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
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

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

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

provided by Google News

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

StarTree Makes Observability Case for Apache Pinot Database
8 May 2024, DevOps.com

Real-Time Analytics for Mobile App Crashes using Apache Pinot
2 November 2023, Uber

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IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

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

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

IBM Brings Back a Netezza, Attacks Yellowbrick
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