IBM Integrated Analytics System vs Teradata comparison

IBM and Teradata are both solutions in the Data Warehouse category. IBM is ranked #20, while Teradata is ranked #3 with an average rating of 7.8. IBM holds a 0.8% mindshare in Data Warehouse, compared to Teradata’s 17.1% mindshare. Additionally, 100% of IBM users are willing to recommend the solution, compared to 87% of Teradata users who would recommend it.

IBM Integrated Analytics Sy...

Read 1 IBM Integrated Analytics System review

278 Views
225 Comparison Views

100% willing to recommend

Teradata

Read 76 Teradata reviews

5,073 Views
3,850 Comparison Views

87% willing to recommend

IBM Integrated Analytics Sy...

Teradata

Comparison Buyer's Guide

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Executive SummaryUpdated on Oct 6, 2024

IBM Integrated Analytics System and Teradata are competing analytics platforms. IBM has an edge in pricing and support, while Teradata's feature set makes the investment worthwhile.

Features: IBM Integrated Analytics System is known for its simplicity, effective data processing, and seamless integration with other IBM solutions. Teradata is recognized for scalability, advanced analytics, and flexibility in large-scale data environments.

Room for Improvement: IBM users seek better reporting tools, enhanced scalability, and improved integration with non-IBM products. Teradata users look for better cost-efficiency, an intuitive setup process, and ease of use enhancements.

Ease of Deployment and Customer Service: IBM's deployment process is smooth, complemented by reliable customer service. Teradata's deployment is more complex, but it's supported by a knowledgeable service team that facilitates transitions.

Pricing and ROI: IBM is favored for competitive setup costs and quick ROI, appealing to budget-conscious businesses. Teradata, though pricier initially, offers enhanced capabilities and promising long-term ROI.

To learn more, read our detailed Data Warehouse Report (Updated: November 2024).

Buyer's Guide

Data Warehouse

November 2024

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Helped 824,067 peers since 2012

Categories and Ranking

IBM Integrated Analytics Sy...

Ranking in Data Warehouse

20th

Average Rating

8.0

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in Data Warehouse

3rd

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (5th), Backup and Recovery (19th), Data Integration (18th), Relational Databases Tools (7th), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of December 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 14.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse

Featured Reviews

it_user258975

Senior Information Management Specialist at a tech services company with 501-1,000 employees

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…

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SurjitChoudhury

Data engineer at Cocos pt

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.

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Comparison Review

it_user232068

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…

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Top Industries

By visitors reading reviews

Manufacturing Company

19%

Computer Software Company

15%

Energy/Utilities Company

13%

Financial Services Firm

13%

Financial Services Firm

26%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

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...

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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...

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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

IBM Netezza Performance Server vs IBM Integrated Analytics System

Compared 100% of the time

More IBM Integrated Analytics System Competitors

Oracle Exadata vs Teradata

Compared 14% of the time

SQL Server vs Teradata

Compared 13% of the time

Snowflake vs Teradata

Compared 8% of the time

MySQL vs Teradata

Compared 8% of the time

Vertica vs Teradata

Compared 5% of the time

More Teradata Competitors

Product Reports

Buyer's Guide

Data Warehouse

November 2024

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Buyer's Guide

Teradata

November 2024

Download Teradata product report

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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IBM

Teradata

Overview

The IBM Smart Analytics System provides analytics capabilities on a data warehouse foundation. This integrated and optimized system combines advanced software with IBM server and storage hardware to address a range of analytics workloads and accelerate deployment to help achieve greater efficiency, lower cost and higher performance.

Teradata is a scalable data analytics platform designed to meet enterprise demands for large-scale data management and processing, focusing on performance, scalability, and security for complex query executions.

As a leading data warehousing solution, Teradata integrates advanced analytics enabling organizations to derive insights from massive datasets. It supports high-volume data workloads with its architecture optimized for analytical queries. Users benefit from its robust scalability, allowing seamless expansion as data grows. Teradata's SQL engine is compatible with a wide range of data types, ensuring flexibility in data analysis. With advanced security measures, it protects sensitive data across various environments, providing peace of mind to users handling critical information.

What are the most important features of Teradata?

Linear Scalability: Easily expands data processing capabilities to handle increasing data loads without performance degradation.
Advanced Analytics: Supports complex analytical operations integrating machine learning and AI for predictive insights.
SQL Compatibility: Offers a comprehensive SQL interface that supports complex queries across diverse data types.
Data Security: Implements rigorous security protocols to protect data integrity and confidentiality.

What benefits and ROI should users look for?

Improved Decision-Making: Derive actionable insights quickly for strategic business decisions.
Cost Efficiency: Optimized resource usage reduces operational costs associated with data processing.
Increased Productivity: Streamlined data operations save time, allowing teams to focus on analysis.
Enhanced Scalability: Seamless growth without significant additional investment as data volumes increase.

Teradata is widely used in industries like finance, telecommunications, and healthcare, where data-driven decisions are critical. Companies leverage its robust analytics capabilities to enhance customer experiences, streamline operations, and ensure compliance with regulatory requirements. In these sectors, quick access to data insights can significantly impact competitive advantage.

Sample Customers

WIdO AOK, EEKA Fashion, SSGC, GS Retail

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