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IBM Netezza VS ClickHouse

Compare IBM Netezza VS ClickHouse and see what are their differences

IBM Netezza logo IBM Netezza

Netezza is a powerful platform that changed the world of data warehousing by introducing one of the world’ first data warehouse appliances.

ClickHouse logo ClickHouse

ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
  • IBM Netezza Landing page
    Landing page //
    2023-08-18
  • ClickHouse Landing page
    Landing page //
    2019-06-18

IBM Netezza videos

Netezza Overview

More videos:

  • Review - Explain about Netezza
  • Review - Get to know the IBM Netezza Performance Server

ClickHouse videos

No ClickHouse videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to IBM Netezza and ClickHouse)
Databases
15 15%
85% 85
Big Data
100 100%
0% 0
Relational Databases
0 0%
100% 100
NoSQL Databases
22 22%
78% 78

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare IBM Netezza and ClickHouse

IBM Netezza Reviews

16 Top Big Data Analytics Tools You Should Know About
The Netezza Performance Server data warehouse system includes SQL that is known as IBM Netezza Structured Query Language (SQL). We can use SQL commands to create and manage the Netezza databases, user access, and permissions for the database. It can also be used to query and modify the contents of the databases.

ClickHouse Reviews

Rockset, ClickHouse, Apache Druid, or Apache Pinot? Which is the best database for customer-facing analytics?
ClickHouse is an open-source, column-oriented, distributed, and OLAP database that’s very easy to set up and maintain. “Because it’s columnar, it’s the best architectural approach for aggregations and for ‘sort by’ on more than one column. It also means that group by’s are very fast. It’s distributed, replication is asynchronous, and it’s OLAP—which means it’s meant for...
Source: embeddable.com
ClickHouse vs TimescaleDB
Recently, TimescaleDB published a blog comparing ClickHouse & TimescaleDB using timescale/tsbs, a timeseries benchmarking framework. I have some experience with PostgreSQL and ClickHouse but never got the chance to play with TimescaleDB. Some of the claims about TimescaleDB made in their post are very bold, that made me even more curious. I thought it’d be a great...
20+ MongoDB Alternatives You Should Know About
ClickHouse may be a great contender for moving analytical workloads from MongoDB. Much faster, and with JSON support and Nested Data Structures, it can be great choice for storing and analyzing document data.
Source: www.percona.com

Social recommendations and mentions

Based on our record, ClickHouse seems to be more popular. It has been mentiond 44 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

IBM Netezza mentions (0)

We have not tracked any mentions of IBM Netezza yet. Tracking of IBM Netezza recommendations started around Mar 2021.

ClickHouse mentions (44)

  • Simplified API Creation and Management: ClickHouse to APISIX Integration Without Code
    In the world of data management and web services, creating and managing APIs can often be a complex and time-consuming task. However, with the right tools, this process can be significantly simplified. In this article, we will explore how to create APIs for fetching data from ClickHouse tables without writing any code and manage these APIs using APISIX. ClickHouse, a fast and open-source columnar database... - Source: dev.to / 23 days ago
  • The 2024 Web Hosting Report
    For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 4 months ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in... - Source: dev.to / 4 months ago
  • Real-Time Data Enrichment and Analytics With RisingWave and ClickHouse
    To achieve seamless real-time data ingestion, transformation, and analytics, a powerful combination to explore is RisingWave and ClickHouse. RisingWave is a PostgreSQL-compatible database specifically designed for stream processing. It excels at ingesting real-time data streams, performing diverse transformations, and enabling instant querying of results. ClickHouse® is a high-performance, column-oriented SQL... - Source: dev.to / 6 months ago
  • Ask HN: Is there a Hacker News takeout to export my comments / upvotes, etc.?
    You can export the whole dataset as described here: https://github.com/ClickHouse/ClickHouse/issues/29693
        curl https://clickhouse.com/ | sh.
    - Source: Hacker News / 6 months ago
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What are some alternatives?

When comparing IBM Netezza and ClickHouse, you can also consider the following products

Amazon Redshift - Learn about Amazon Redshift cloud data warehouse.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

LibreOffice - Base - Base, database, database frontend, LibreOffice, ODF, Open Standards, SQL, ODBC

MySQL - The world's most popular open source database

Microsoft Office Access - Access is now much more than a way to create desktop databases. It’s an easy-to-use tool for quickly creating browser-based database applications.

Apache Doris - Apache Doris is an open-source real-time data warehouse for big data analytics.