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Teradata vs WP Bolt comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Apr 5, 2026

Review summaries and opinions

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

Categories and Ranking

Teradata
Ranking in Data Warehouse
2nd
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
83
Ranking in other categories
Customer Experience Management (5th), Backup and Recovery (10th), Data Integration (14th), Relational Databases Tools (5th), BI (Business Intelligence) Tools (9th), Marketing Management (4th), Cloud Data Warehouse (2nd), Database Management Systems (DBMS) (5th)
WP Bolt
Ranking in Data Warehouse
27th
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2026, in the Data Warehouse category, the mindshare of Teradata is 8.7%, down from 13.1% compared to the previous year. The mindshare of WP Bolt is 1.6%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Warehouse Mindshare Distribution
ProductMindshare (%)
Teradata8.7%
WP Bolt1.6%
Other89.7%
Data Warehouse
 

Featured Reviews

David Durand Velásquez - PeerSpot reviewer
Engineers at a consultancy with 11-50 employees
Delivers consistent performance and enables advanced analytics across complex data environments
Teradata stands out as a solid platform for managing and analyzing large volumes of data. Its architecture allows information to be processed efficiently while maintaining stable performance, even in highly demanding environments. One of its most notable strengths is the ability to run complex queries at high speed, which is essential for organizations that require timely and reliable analytics. Teradata offers a well-integrated ecosystem that supports working with different types of data and enables scalability as organizational needs grow. Its focus on advanced analytics, integration with modern business intelligence tools, and the ability to operate both on-premise and in the cloud make it a versatile solution for data warehousing and large-scale processing. Teradata's stability, technological maturity, and the availability of strong documentation and best practices are noteworthy. I consider Teradata to be a tool with great potential for any organization looking to enhance its analytical capabilities, optimize data processing, and move toward more data-driven decision-making. Teradata stands out as a solid platform for managing a large volume of data in different projects. Its architecture allows information to be processed efficiently while maintaining stable performance, even in high-demanding environments. A well-integrated AI ecosystem that supports working with different types of data and enables scalability as organizational needs grow across different kinds of enterprises or organizations. The focus on advanced analytics integration with modern business intelligence tools is particularly valuable. Teradata combines a powerful parallel process and optimizing SQL engine with a highly scalable architecture allowing businesses to execute complex queries and analytics in real-time. It supports multi-cloud, hybrid, and on-premise environments, giving organizations flexibility to choose the setup that best aligns with their strategy. One of the biggest strengths is the ability to unify disparate data sources and support high concurrency, enabling different teams, such as analytics, operations, BI, and data science, to access consistent, trusted data across the enterprise.
it_user665328 - PeerSpot reviewer
ETL Developer at a music company with 501-1,000 employees
the most useful feature of the product is object imaging. It is the champion in the world of RDBMS.
Although they already have patches to address the instability of CORV (Create or Replace Views) CASCADE, I believe this is the area that should receive most attention. I am, however, still not sure if the patch has officially been recognised and deployed as part of their version updates. There are a few critical issues/bugs that we have experienced on our production environment, which required intervention from Kognitio. As one of Kognitio's biggest clients, their response times were quick and patches were also quick to be released to address production issues. Also, slabs management seems to be, or can be, a very hands-on tasks especially when reaching its capacity. It will be every WX2/KAP developer’s or DBA’s paradise if the product can be configured in this area to be fully/semi-automated.

Quotes from Members

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

Pros

"The feature that we find most valuable is its ability to perform Massive Parallel Processing."
"There are two very useful features: one is the fast data input for more or less any online data, and two, it also has a lot of tools for data engineering or data manipulation that are compatible."
"The functionality of the solution is excellent."
"It has reduced a lot of reworking on maintaining indexes, partitions, etc."
"In Data Lab, you can schedule any testing you want to do in production. You can take a small subset of data from production, copy it there, and run all your tests. It reduces your testing costs because it's all in the lab."
"It's the same as your visual database. I like the fast load feature for data, the BTQ solution is very good, and storage procedures are very fast."
"If the priority is to find the best tool that can be relied on with less maintenance and good performance, Teradata is definitely a good option, but again, homework must be done to see which one suits the data workloads."
"I like this solution's ease of design and the fact that its performance is quite good. It is stable as well."
"In the world of RDBMS, WX2/KAP is, I believe, the champion, or should be if not already!"
 

Cons

"Teradata needs to pay attention to the cloud-based solution to make sure it runs smoothly."
"The usability could be a bit better. It could be a bit more user-friendly."
"I'm not sure about the unstructured data management capabilities. It could be improved."
"Teradata's pricing is quite high compared to Redshift, Synapse, or GCP alternatives."
"Azure Synapse SQL has evolved from a solely dedicated support tool to a data lake. It can store data from multiple systems, not just traditional database management systems. On the other hand, Teradata has limitations in loading flat files or unstructured data directly into its warehouse. In Azure Synapse SQL, we can implement machine learning using Python scripts. Additionally, Azure Synapse SQL offers advanced analytical capabilities compared to Teradata. Teradata is also expensive."
"Stability-wise, we have had some issues with automation and the ability to handle large datasets."
"Teradata is a bit late for the cloud."
"The reporting side wasn't very good in the past, but with the latest versions, it's getting better. Still, the friendliness of the PDC reporting and functionality needs to be improved."
"It does not have the robustness or stability like of Oracle or Teradata; the upper right quadrant."
 

Pricing and Cost Advice

"The cost is significantly high."
"We are looking for a more flexible cost model for the next version that we use, whether it be cloud or on-premise."
"The solution requires a license."
"The price of Teradata could be less expensive."
"Teradata's licensing is on the expensive side."
"In this day and age, we want to get things done quickly. So, we go to the AWS Marketplace."
"Price is quite high, so if it is really possible to use other solutions (e.g. you do not have strict requirements for performance and huge data volumes), it might be better to look at alternatives from the RDBMS world."
"It's a very expensive product."
Information not available
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Comparison Review

it_user232068 - PeerSpot reviewer
Senior Data Architect at a pharma/biotech company with 1,001-5,000 employees
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
Financial Services Firm
17%
Outsourcing Company
10%
Manufacturing Company
8%
Construction Company
8%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise13
Large Enterprise53
No data available
 

Questions from the Community

Comparing Teradata and Oracle Database, which product do you think is better and why?
I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...
Which companies use Teradata and who is it most suitable for?
Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...
Is Teradata a difficult solution to work with?
Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...
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Comparisons

 

Also Known As

IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture, Teradata Vantage Enterprise (DIY)
Kognitio WX2, WX2
 

Overview

 

Sample Customers

Netflix
Aimia, Bed Bath & Beyond, bet365, Blueberry Wave, British Telecom, Ellerines, Everyclick, Nectar Italia, PlaceIQ, ScottishPower, Segmetrix, Tattershall Castle Group, Vocal Planet, VivaKi, Willard Bishop
Find out what your peers are saying about Snowflake Computing, Teradata, Oracle and others in Data Warehouse. Updated: September 2026.
913,683 professionals have used our research since 2012.