SAS Access vs Teradata comparison

SAS and Teradata are both solutions in the Data Integration category. SAS is ranked #56, while Teradata is ranked #17 with an average rating of 7.5. SAS holds a 0.3% mindshare in DI, compared to Teradata’s 1.0% mindshare. Additionally, 100% of SAS users are willing to recommend the solution, compared to 87% of Teradata users who would recommend it.

SAS Access

Read 3 SAS Access reviews

265 Views
215 Comparison Views

100% willing to recommend

Teradata

Read 76 Teradata reviews

867 Views
633 Comparison Views

87% willing to recommend

SAS Access

Teradata

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Executive SummaryUpdated on Apr 20, 2025

SAS Access and Teradata are competing solutions in data management and analytics. Teradata gains an edge due to its superior features, making it a valuable investment.

Features: SAS Access integrates with numerous data sources, emphasizes user-friendly data preparation, and is adaptable across various platforms. Teradata supports large-scale data environments, handles extensive datasets efficiently, and has robust analytics capabilities.

Ease of Deployment and Customer Service:SAS Access offers seamless integration with simpler deployment processes and comprehensive customer support. Teradata, although requiring a sophisticated setup, provides strong support for complex data environments.

Pricing and ROI: SAS Access offers reasonable setup costs with quick ROI, serving as a budget-friendly choice. Teradata, with higher upfront costs, justifies this with powerful features and long-term gains.

To learn more, read our detailed SAS Access vs. Teradata Report (Updated: April 2025).

Buyer's Guide

SAS Access vs. Teradata

April 2025

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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

SAS Access

Ranking in Data Integration

56th

Average Rating

9.0

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in Data Integration

17th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (20th), Relational Databases Tools (8th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of May 2025, in the Data Integration category, the mindshare of SAS Access is 0.3%, up from 0.2% compared to the previous year. The mindshare of Teradata is 1.0%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Robert Heck

Co Owner at Hecht und Heck GmbH

The solution is stable, scalable, and flexible

I rate the solution eight out of ten. The number of people required to maintain the solution is dependent on the other applications running. The solution in itself does not require a lot of maintenance. The solution is flexible and I recommend it when you have more complex applications with special requirements.

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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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Quotes from Members

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

Pros

"The most valuable aspect of the solution is the ease of access to the data in those databases."

"The most valuable part of SAS/ACCESS is what it is made for: connecting to remote systems that are not part of your physical SAS environment."

"The most valuable feature is you have native access to the external databases."

"The most valuable feature of Teradata is the quick processing of large data."

"I like writing preformance queries for preprocessing on AWS Cloud."

"The most valuable features are the large volume of data and the structuring of the data to optimize it and get very optimal data warehouse solutions for customers."

"I like this solution's ease of design and the fact that its performance is quite good. It is stable as well."

"Teradata's most valuable feature is that it's easy to use."

"The feature that we find most valuable is its ability to perform Massive Parallel Processing."

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

"Teradata's capabilities enhance data management efficiency, support scalability, and contribute to faster query performance."

More Teradata pros

Cons

"The solution can provide access to the newer databases that come out sooner."

"I can't really recall any missing feature or general improvement that is needed. We don't really add too many new kinds of databases and therefore our needs are already met."

"The pricing model needs to be reconsidered and adjusted."

"It could be a bit more user-friendly."

"I would like to see more integration with many different types of data."

"Teradata hardly supports unstructured data or semi-structured data"

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

"The setup is not straightforward."

"Teradata can improve the way it handles big data and unstructured data."

"There are some ways that the handling of unstructured data could be improved."

"Stability-wise, we have had some issues with automation and the ability to handle large datasets."

More Teradata cons

Pricing and Cost Advice

"The pricing model is complex and is based on modular packages as well as the size of the applicable environment."

"The solution's pricing and licensing are expensive."

"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."

"Users have to pay a yearly licensing fee for Teradata IntelliFlex, which is very expensive."

"When looking into implementing this product, pricing is the main issue followed by technical expertise."

"The cost is substantial, totaling around $1.2 million, solely dedicated to upgrading the hardware."

"Teradata used to be expensive, but they have been lowering their prices."

"The solution requires a license."

"Teradata is expensive, so it's typically marketed to big customers. However, there have been some changes, and Teradata is now offering more flexible pricing models and equipment leasing. They've added pay-as-you-go and cloud models, so it's changing, but Teradata is generally known as an expensive high-end product."

"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."

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…

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Top Industries

By visitors reading reviews

Financial Services Firm

26%

Computer Software Company

10%

Manufacturing Company

Insurance Company

Financial Services Firm

26%

Computer Software Company

11%

Healthcare Company

Manufacturing 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

No data available

Oracle Exadata vs Teradata

Compared 13% of the time

SQL Server vs Teradata

Compared 10% of the time

Snowflake vs Teradata

Compared 7% of the time

IBM Db2 Database vs Teradata

Compared 6% of the time

MySQL vs Teradata

Compared 6% of the time

More Teradata Competitors

Product Reports

Buyer's Guide

Data Integration

May 2025

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Buyer's Guide

Teradata

April 2025

Download Teradata product report

Also Known As

SAS/Access

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

Overview

SAS/ACCESS is an out-of-the-box solution for integrating SAS and third-party databases. You can read, write and update data regardless of the database or platform. Because the data appears native to SAS, there is no need to learn Structured Query Language (SQL) or any other database-specific query languages.

SAS

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.

Teradata

Sample Customers

Los Angeles County, West Midlands Police, Credit Guarantee Corporation, Canada Post, Allianz Global Corporate & Specialty

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Buyer's Guide

SAS Access vs. Teradata

April 2025

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