IBM Integrated Analytics System vs Snowflake vs Teradata comparison

IBM Integrated Analytics Sy...

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Snowflake

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Executive Summary

We performed a comparison between IBM Integrated Analytics System, Snowflake, and Teradata based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse.

To learn more, read our detailed Data Warehouse Report (Updated: March 2026).

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Data Warehouse

March 2026

Helped 892,487 peers since 2012

Review summaries and opinions

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

Mindshare comparison

As of May 2026, in the Data Warehouse category, the mindshare of IBM Integrated Analytics System is 1.8%, up from 0.9% compared to the previous year. The mindshare of Snowflake is 9.3%, down from 13.8% compared to the previous year. The mindshare of Teradata is 8.8%, down from 15.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Snowflake	9.3%
Teradata	8.8%
IBM Integrated Analytics System	1.8%
Other	80.1%

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…

Have prioritized security while managing multi-agent data migration and cloud adoption

SunilPatil1

Asset Builder at Genpact - Headstrong

We utilize Time Travel with Snowflake because this is a very useful feature. Everyone finds it crucial because in conventional data platforms, it's very difficult to handle these kinds of things. This feature is essential, though I don't have the use cases currently; it is just there for implementation. Regarding Snowflake's automated scaling and suspension features, this auto-scaling is very significant. We had a comparison with Databricks and Snowflake a few months back, and this auto-scaling takes an edge within Snowflake; that's what our observation reflects.

Delivers consistent performance and enables advanced analytics across complex data environments

David Durand Velásquez

Engineers at a consultancy with 11-50 employees

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.

More Snowflake pricing and cost advice

Quotes from Members

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

Pros

"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."

"The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."

"It was relatively easy to use, and it was easy for people to convert to it."

"The most valuable feature of Snowflake is it's an all-in-one data warehousing solution."

"The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management. It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure."

"Snowflake is easy for business users to implement, allowing them to start small and grow big."

"We have seen ROI when using Snowflake based on the insights we get."

"The most valuable features of Snowflake are its performance and power."

"The way Snowflake has emerged in the past few years is impressive."

More Snowflake pros

"Teradata features high productivity and reliability because it has several redundancy options, so the system is always up and running."

"We have SAP IQ data warehouse now and I don't have a major problem."

"Improved performance of ETL procedures, reporting."

"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's very, very fast"

"It handles large amounts of information with a linear performance increase, in relation to a HW investment."

"It is a stable solution. Stability-wise, I rate the solution a nine out of ten."

"Performance-wise, Teradata beats everything."

More Teradata pros

Cons

"The HA - it's a good solution, but I feel IBM should provide the necessary scripts so you can destroy the TSA domain and rebuild it easily."

"The UI could improve because sometimes in the security query the UI freezes."

"The stability has been phenomenal up until lately. We haven't had any issues until the last month."

"From an improvement perspective, Snowflake can evolve in terms of writing costly, expensive queries with less cost and try to see if pipeline development can be made a little easier."

"They don't have any SLAs in place. It would be better if they did."

"We would like to see more security including more masking and more encryption at the database level."

"This solution could be improved by offering machine learning apps."

"For the Snowflake database, there should be some third-party features for the ETL. It would also be good to be able to use some kind of controls to get the data either from another database or a flat file. Its price should be improved. It should be cheaper than Microsoft."

"The solution could improve by allowing non-structured data, such as PDFs, images, or videos. We cannot see the data."

More Snowflake cons

"Query language and its functionality are rather limited, compared to Oracle or even SQL Server. However, it is possible to perform any kind of logic in it (though some workarounds may be required)."

"I'd like to see better processing on a transactional level and star schema optimization."

"The cloud is the new challenge and the new opportunity."

"The increasing volumes of data demand more and more performance."

"Teradata's UI could be more user-friendly."

"Data synchronization to the DR site."

"The capability to implement it with comparable performance across various private cloud environments, ensuring adaptability to different infrastructure setups would be beneficial."

"I think the UI is not there yet. It could be improved by being more user-friendly."

More Teradata cons

Pricing and Cost Advice

Information not available

"It is on a monthly basis. It is based on your usage. There are no additional costs from the point of the licensing fee. We do give some kind of evaluation to the customers about how much it is going to be. You can decide in Snowflake the virtual machine that you are using for customers. There are several kinds of virtual machines that you can use. It is similar to the clothing sizes: small to extra large. If you need more power in the coming month, you can decide in advance and take a more powerful machine. You can just select it from the platform. You can also decide which machine you want to take for extracting data."

"The solution is costly, making it unsuitable for midsize organizations due to its price."

"There is a separation of storage and compute, so you only pay for what you use."

"You need to be aware of the bloating costs. It is easy to use, but if you don't use it wisely, then your monthly bill can bloat a lot. You need to be a bit aware of its consumption cost."

"It is pay-as-you-go. Its cost is in the medium range."

"Oracle is less expensive than Snowflake."

"You pay based on the data that you are storing in the data warehouse and there are no maintenance costs."

"It is hard to say because we're usually engaged in the transition as opposed to the long term. Their storage costs are easily within pennies of what AWS S3 would normally cost. Most of the clients I've been working with are in the financial sector, and they're relatively small. I would put them in an SMB connection. The first thing we have to bring up for people is that they're going to build this. They shouldn't store their data in S3. They should pipeline directly into Snowflake and use it on their storage. So, the cost is a big issue because these are small to medium size companies, and that is the biggest thing we had to price point for them."

"The tool costs about 30,000 euros a month, while Azure Synapse SQL only costs 10,000."

"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."

"In this day and age, we want to get things done quickly. So, we go to the AWS Marketplace."

"The solution requires a license."

"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."

"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."

"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."

"The price of the solution could be reduced, it is expensive."

More Teradata pricing and cost advice

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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…

What is your experience regarding pricing and costs for Snowflake?

Top Industries

By visitors reading reviews

No data available

Financial Services Firm

20%

Manufacturing Company

Computer Software Company

Healthcare Company

Financial Services Firm

20%

Manufacturing Company

Construction Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	30
Midsize Enterprise	20
Large Enterprise	58

By reviewers
Company Size	Count
Small Business	28
Midsize Enterprise	13
Large Enterprise	52

Questions from the Community

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For pricing, setup cost, and licensing, everything is managed smoothly. Regarding licensing, it is inexpensive. The s...

What needs improvement with Snowflake?

Snowflake is already quite improved, but they have recently introduced AI features. AI integration would be beneficia...

What is your primary use case for Snowflake?

Snowflake is primarily used to handle the data warehousing part, for creating data modeling, and also keeping the raw...

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 d...

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 ...

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 ...

IBM Netezza Performance Server vs IBM Integrated Analytics System

Comparisons

Compared 16% of the time

Oracle Big Data Appliance vs IBM Integrated Analytics System

Compared 16% of the time

Oracle Exadata vs IBM Integrated Analytics System

Compared 13% of the time

OpenText Analytics Database (Vertica) vs IBM Integrated Analytics System

Compared 9% of the time

SAP IQ vs IBM Integrated Analytics System

Compared 9% of the time

More IBM Integrated Analytics System Competitors

Microsoft Azure Synapse Analytics vs Snowflake

Compared 5% of the time

Amazon Redshift vs Snowflake

Compared 5% of the time

Databricks vs Snowflake

Compared 5% of the time

Dremio vs Snowflake

Compared 4% of the time

Azure Data Factory vs Snowflake

Compared 4% of the time

More Snowflake Competitors

Oracle Database vs Teradata

Compared 4% of the time

SQL Server vs Teradata

Compared 4% of the time

Oracle Exadata vs Teradata

Compared 3% of the time

MySQL vs Teradata

Compared 3% of the time

IBM Db2 Database vs Teradata

Compared 2% of the time

More Teradata Competitors

Product Reports

Download IBM Integrated Analytics System product report

Data Warehouse

March 2026

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Snowflake

April 2026

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April 2026

Also Known As

Smart Analytics System, IBM Smart Analytics System

Snowflake Computing, Snowflake Data Cloud

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

Overview

IBM Integrated Analytics System provides an advanced data analytics platform tailored for organizations seeking powerful insights into their data operations, enabling seamless data management and analysis.

With IBM Integrated Analytics System, organizations achieve enhanced data processing capabilities through a combination of sophisticated analytics and integrated hardware. Designed to handle large datasets efficiently, it supports a wide range of analytics workloads with high performance and reliability.

What are the most important features of IBM Integrated Analytics System?

Integrated Hardware: Ensures optimal performance by combining hardware with analytics software.
Scalability: Easily scales to meet increasing data demands.
Advanced Analytics: Offers a comprehensive set of analytic tools for deeper insights.
Data Virtualization: Allows access to data across different platforms without moving it.
Cloud Compatibility: Supports integration with cloud environments for flexible deployment.

What benefits or ROI should users look for in reviews?

Increased Efficiency: Streamlines data processing to enhance productivity.
Cost Savings: Reduces expenditure through integrated systems.
Flexibility: Adapts to different industries and workloads with ease.
Improved Decision-Making: Provides actionable insights that drive strategic actions.
Data Integrity: Ensures accurate and reliable data handling.

IBM Integrated Analytics System finds application across industries such as finance, healthcare, and retail, where it supports tasks like real-time data processing, customer analytics, and risk management, aiding companies in making informed business decisions and maintaining a competitive edge.

IBM

Snowflake provides a modern data warehousing solution with features designed for seamless integration, scalability, and consumption-based pricing. It handles large datasets efficiently, making it a market leader for businesses migrating to the cloud.

Snowflake offers a flexible architecture that separates storage and compute resources, supporting efficient ETL jobs. Known for scalability and ease of use, it features built-in time zone conversion and robust data sharing capabilities. Its enhanced security, performance, and ability to handle semi-structured data are notable. Users suggest improvements in UI, pricing, on-premises integration, and data science functions, while calling for better transaction performance and machine learning capabilities. Users benefit from effective SQL querying, real-time analytics, and sharing options, supporting comprehensive data analysis with tools like Tableau and Power BI.

What are Snowflake's Key Features?

Scalability: Easily adjusts to handle growing data volumes.
Seamless Integration: Works with a wide range of platforms.
Consumption-Based Costs: Pay only for what you use.
Time Travel: Access historical data effortlessly.
Data Sharing: Secure and efficient sharing of datasets.
Time Zone Conversion: Built-in feature for global operations.
Security: Robust measures to protect sensitive information.
Compute and Storage Separation: Independent scaling for optimal performance.

What Benefits Should You Look for?

Cost Efficiency: Optimized pricing models for minimal waste.
Enhanced Performance: Fast queries and processing times.
Flexibility: Handles both structured and semi-structured data.
Analytics Capabilities: Supports advanced data analysis and reporting.

In industries like finance, healthcare, and retail, Snowflake's flexible data warehousing and analytics capabilities facilitate cloud migration, streamline data storage, and allow organizations to consolidate data from multiple sources for advanced insights and AI-driven strategies. Its integration with analytics tools supports comprehensive data analysis and reporting tasks.

Snowflake Computing

Teradata is a powerful tool for handling substantial data volumes with its parallel processing architecture, supporting both cloud and on-premise environments efficiently. It offers impressive capabilities for fast query processing, data integration, and real-time reporting, making it suitable for diverse industrial applications.

Known for its robust parallel processing capabilities, Teradata effectively manages large datasets and provides adaptable deployment across cloud and on-premise setups. It enhances performance and scalability with features like advanced query tuning, workload management, and strong security. Users appreciate its ease of use and automation features which support real-time data reporting. The optimizer and intelligent partitioning help improve query speed and efficiency, while multi-temperature data management optimizes data handling.

What are the key features of Teradata?

Parallel Processing Architecture: Enables efficient handling of substantial data volumes.
Cloud and On-Premise Deployment: Offers seamless adaptability across environments.
Query Tuning: Improves speed and performance of data retrieval processes.
Workload Management: Ensures optimal resource allocation for enhanced performance.
Robust Security: Provides high levels of data protection and system integrity.
Data Integration: Facilitates cohesive data management from multiple sources.
Automation for Real-time Reporting: Enhances timely data insights and decision-making.
Optimizer and Intelligent Partitioning: Further increase query speed and system efficiency.
Multi-Temperature Data Management: Optimizes the handling and retrieval of data.

What benefits and ROI do users look for?

Efficient Data Management: Facilitates smooth integration and processing of diverse data sets.
Scalability: Easy adjustment to increasing or decreasing data requirements.
Improved Performance: Fast query speeds and optimized resource use.
Comprehensive Security: Safeguards data integrity and accessibility.
Ease of Use: Simplifies data handling and operational processes.

In the finance, retail, and government sectors, Teradata is employed for data warehousing, business intelligence, and analytical processing. It handles vast datasets for activities like customer behavior modeling and enterprise data integration. Supporting efficient reporting and analytics, Teradata enhances data storage and processing, whether deployed on-premise or on cloud platforms.