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BigQuery vs IBM Netezza Performance Server comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
7.4
Organizations experienced improved performance and cost savings after adopting BigQuery, achieving a 75% cost reduction and efficient data management.
Sentiment score
7.1
IBM Netezza Performance Server improves data query speed and efficiency, enhancing business performance and cost savings through compression.
 

Customer Service

Sentiment score
7.2
Customers generally find BigQuery support helpful, but integration challenges and resource availability need improvement despite positive responsiveness.
Sentiment score
6.4
IBM Netezza Performance Server praised for knowledgeable support; mixed feedback on resolution speed post-acquisition, yet communication remains consistent.
I have been self-taught and I have been able to handle all my problems alone.
rating the customer support at ten points out of ten
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
 

Scalability Issues

Sentiment score
8.0
BigQuery offers impressive scalability and efficiency for large data, but may be costly and present integration challenges for smaller users.
Sentiment score
6.1
IBM Netezza struggles with scalability, requiring extra hardware for expansion, prompting users to consider cloud alternatives for growth.
It is a 10 out of 10 in terms of scalability.
The scalability is definitely good because we are migrating to the cloud since the computers on the premises or the big database we need are no longer enough.
It is provided as a pre-configured box, and scaling is not an option.
 

Stability Issues

Sentiment score
8.5
BigQuery is highly stable and reliable for cloud data analytics, efficiently handling large volumes with minor issues.
Sentiment score
7.8
IBM Netezza Performance Server is stable, offering high uptime and reliable performance, with occasional issues due to maintenance or compatibility.
 

Room For Improvement

BigQuery users face challenges with migration, integration, cost, scaling, user interfaces, and call for better machine learning capabilities.
IBM Netezza struggles with scalability, user interface, query performance, big data support, and high costs, needing better tools and integration.
Troubleshooting requires opening each pipeline individually, which is time-consuming.
BigQuery is already integrating Gemini AI into the data extraction process directly in order to reduce costs.
In general, if I know SQL and start playing around, it will start making sense.
The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment.
 

Setup Cost

BigQuery offers flexible, pay-as-you-go pricing based on data usage, with low storage costs and adaptable enterprise plans.
IBM Netezza offers high performance and low maintenance but is considered costly, especially for mid-sized organizations, with significant licensing fees.
Being able to optimize the queries to data is critical. Otherwise, you could spend a fortune.
The price is perceived as expensive, rated at eight out of ten in terms of costliness.
 

Valuable Features

BigQuery excels in scalability, performance, cost-efficiency, and integration with Google products, making it ideal for complex data analyses.
IBM Netezza Performance Server delivers fast analytics, ease of use, robust support, and efficient data warehousing with minimal maintenance.
It is really fast because it can process millions of rows in just a matter of one or two seconds.
The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data.
BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes.
It operates as a high-speed data warehouse, which is essential for handling big data.
 

Categories and Ranking

BigQuery
Average Rating
8.2
Reviews Sentiment
7.2
Number of Reviews
41
Ranking in other categories
Cloud Data Warehouse (3rd)
IBM Netezza Performance Server
Average Rating
7.8
Reviews Sentiment
6.9
Number of Reviews
45
Ranking in other categories
Data Warehouse (12th), Hadoop (7th)
 

Featured Reviews

Luís Silva - PeerSpot reviewer
Handles large data sets efficiently and offers flexible data management capabilities
The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data. It is kind of difficult to explain, but structured data and the ability to handle large data sets are key features. The data integration capabilities in BigQuery were, in fact, an issue at the beginning. There are two types of integrations. As long as integration is within Google, it is pretty simple. When you start to try to connect external clients to that data, it becomes more complex. It is not related to BigQuery, it is related to Google security model, which is not easy to manage. I would not call it an integration issue of BigQuery, I would call it an integration issue of Google security model.
Shiv Subramaniam Koduvayur - PeerSpot reviewer
Parallel data processing streamlines operations while cost and cloud integration challenge adoption
The cost of the solution is on the more expensive side, which is a concern for me. Additionally, its promotion and interaction with cloud applications are limited. The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment. For the cost to be reduced, it should match competitors. Many features need to be incorporated on the cloud.
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
869,566 professionals have used our research since 2012.
 

Comparison Review

it_user232068 - PeerSpot reviewer
Aug 5, 2015
Netezza vs. Teradata
Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…
 

Top Industries

By visitors reading reviews
Computer Software Company
16%
Financial Services Firm
14%
Manufacturing Company
11%
Retailer
7%
Financial Services Firm
22%
Insurance Company
7%
Manufacturing Company
7%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise9
Large Enterprise20
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise5
Large Enterprise33
 

Questions from the Community

What do you like most about BigQuery?
The initial setup process is easy.
What is your experience regarding pricing and costs for BigQuery?
I believe the cost of BigQuery is competitive versus the alternatives in the market, but it can become expensive if the tool is not used properly. It is on a per-consumption basis, the billing, so ...
What needs improvement with BigQuery?
I have not used BigQuery for AI and machine learning projects myself. I know how to use it, and I can see where it would be useful, but so far, in my projects, I have not included a BigQuery compon...
What needs improvement with IBM Netezza Performance Server?
The cost of the solution is on the more expensive side, which is a concern for me. Additionally, its promotion and interaction with cloud applications are limited. The cloud version is only availab...
What advice do you have for others considering IBM Netezza Performance Server?
The solution has generally received positive feedback from me and is recommended for continued use by end users. However, the product cost is high compared to others in the market, and this cost ha...
 

Also Known As

No data available
Netezza Performance Server, Netezza, Netezza Analytics
 

Overview

 

Sample Customers

Information Not Available
Seattle Childrens Hospital, Carphone Warehouse, Vanderbilt University School of Medicine, Battelle, Start Today Co. Ltd., Kelley Blue Book, Trident Marketing, Elisa Corporation, Catalina Marketing, iBasis, Barnes & Noble, Qualcomm, MediaMath, Acxiom, iBasis, Foxwoods
Find out what your peers are saying about BigQuery vs. IBM Netezza Performance Server and other solutions. Updated: September 2025.
869,566 professionals have used our research since 2012.