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DBMS > Apache Impala vs. ClickHouse vs. Netezza

System Properties Comparison Apache Impala vs. ClickHouse vs. Netezza

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonClickHouse  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.Data warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score15.55
Rank#38  Overall
#23  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websiteimpala.apache.orgclickhouse.comwww.ibm.com/­products/­netezza
Technical documentationimpala.apache.org/­impala-docs.htmlclickhouse.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaClickhouse Inc.IBM
Initial release201320162000
Current release4.1.0, June 2022v24.4.1.2088-stable, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Implementation languageC++C++
Server operating systemsLinuxFreeBSD
Linux
macOS
Linux infoincluded in appliance
Data schemeyesyesyes
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsClose to ANSI SQL (SQL/JSON + extensions)yes
APIs and other access methodsJDBC
ODBC
gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Rust
Scala info3rd party library
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingkey based and customSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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 persistentyesyesyes
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 for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.Users with fine-grained authorization concept

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Related products and services
3rd partiesDoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
» more

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaClickHouseNetezza infoAlso called PureData System for Analytics by IBM
Recent citations in the news

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

Cloudera Bringing Impala to AWS Cloud
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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

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Why Clickhouse Should Be Your Next Database
6 July 2023, The New Stack

ClickHouse Cloud & Amazon S3 Express One Zone: Making a blazing fast analytical database even faster | Amazon ...
28 November 2023, AWS Blog

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5 June 2024, Phoronix

A 1000x Faster Database Solution: ClickHouse’s Aaron Katz
1 November 2023, GrowthCap

From Open Source to SaaS: the Journey of ClickHouse
16 January 2024, InfoQ.com

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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

Netezza Performance Server
12 August 2020, IBM

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

provided by Google News



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