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IBM Integrated Analytics System vs Teradata comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Oct 6, 2024
 

Categories and Ranking

IBM Integrated Analytics Sy...
Ranking in Data Warehouse
20th
Average Rating
8.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Teradata
Ranking in Data Warehouse
3rd
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
76
Ranking in other categories
Customer Experience Management (3rd), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)
 

Mindshare comparison

As of November 2024, in the Data Warehouse category, the mindshare of IBM Integrated Analytics System is 0.8%, down from 1.0% compared to the previous year. The mindshare of Teradata is 17.1%, up from 14.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Warehouse
 

Featured Reviews

it_user258975 - PeerSpot reviewer
Jun 24, 2015
They deliver a canned, scalable solution, but I would like to see the TSA scripts available publicly.
With a solid DB2 foundation, it performs incredibly and I recently implemented the new BLU Acceleration, and was dumbfounded that hour-long queries took minutes, in the correct scenario, of course. From a consultant point of view, I can step in and immediately know the system. I do not…
SurjitChoudhury - PeerSpot reviewer
Feb 20, 2024
Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities
We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.

Quotes from Members

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

Pricing and Cost Advice

Information not available
"The cost is significantly high."
"​When looking into implementing this product, pricing is the main issue followed by technical expertise​."
"Teradata is expensive but gives value for money, especially if you don't want to move your data to the cloud."
"Teradata is currently making improvements in this area."
"Teradata pricing is fine, and it's competitive with all the legacy models. On a scale of one to five, with one being the worst and five being the best, I'm giving Teradata a three, because it can be a little expensive, when compared to other solutions."
"In this day and age, we want to get things done quickly. So, we go to the AWS Marketplace."
"We had a lot of parties involved when purchasing from the AWS Marketplace. They are very flexible and aggressive in trying to close the deal. They are good at what they have to offer and listening to the customer. It's a two-way street."
"Teradata's licensing is on the expensive side."
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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
Manufacturing Company
20%
Computer Software Company
15%
Energy/Utilities Company
14%
Financial Services Firm
14%
Financial Services Firm
26%
Computer Software Company
10%
Manufacturing Company
8%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

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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,...
 

Also Known As

Smart Analytics System, IBM Smart Analytics System
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture
 

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Overview

 

Sample Customers

WIdO AOK, EEKA Fashion, SSGC, GS Retail
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Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse. Updated: October 2024.
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