Amazon Redshift vs Teradata comparison

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Executive SummaryUpdated on Oct 6, 2024

Teradata and Amazon Redshift are competitive platforms in the data warehousing category. Amazon Redshift seems to have the upper hand in scalability and integration, while Teradata is favored for its analytical capabilities and security.

Features: Teradata offers advanced analytical processing, comprehensive security controls, and robust analytical capabilities. Amazon Redshift provides unmatched scalability, seamless integration with AWS services, and efficient handling of large data volumes.

Room for Improvement: Teradata can enhance its cost-effectiveness due to high licensing fees and flexibility in performance analytics. Amazon Redshift could improve its query performance and expand support for more complex queries as well as offer greater flexibility in performance analytics.

Ease of Deployment and Customer Service: Teradata features detailed documentation, though it has a steep learning curve during deployment, and users report personalized support experiences. Amazon Redshift offers quick deployment processes and comprehensive customer service support through AWS integration, easing the setup process.

Pricing and ROI: Teradata involves higher setup costs, impacting initial financial investment, yet users note a good long-term ROI with its advanced analytics. Amazon Redshift is considered more budget-friendly with its pay-as-you-go pricing model, providing strong ROI through efficient deployment.

To learn more, read our detailed Amazon Redshift vs. Teradata Report (Updated: October 2024).

Amazon Redshift vs. Teradata

October 2024

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Categories and Ranking

Amazon Redshift

Ranking in Cloud Data Warehouse

4th

Average Rating

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in Cloud Data Warehouse

6th

Average Rating

8.2

Number of Reviews

Ranking in other categories

Customer Experience Management (3rd), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th)

Featured Reviews

Ved Prakash Yadav

Senior Data Platform Manager at a manufacturing company with 10,001+ employees

Apr 10, 2024

Works as a data warehouse system and collects data from different sources

Amazon Redshift serves as our data warehouse system. We collect data from various sources, including 153 streams. We gather companies' data for rating, deployment, and stock market analysis. We then push this data onto Amazon Redshift, which Power BI, Tableau, and even Google Looker use for…

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SurjitChoudhury

Data engineer at Cocos pt

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.

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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 feature is its scalability."

"The most valuable features are that it's easy to set up and easy to connect the many tools that connect to it."

"The solution's speed, stability, and user concurrency have been very good."

"Redshift's versioning and data security are the two most critical features. When migrating into the cloud, it's vital to secure the data. The encryption and security are there."

"It allows you write complex queries and perform row by row processes."

"Redshift's Excel features are handy. Redshift spectrum allows you to directly query the data on an Excel sheet. Now, SQL Server also allows this, but Redshift has many more features."

"Its simplicity in configuration, cost-effectiveness due to being in the cloud and close to our data sources, and the fact that it's a managed service that is scalable and reliable are highly valuable."

"The most valuable feature of Amazon Redshift is its ability to handle really large sets of data."

More Amazon Redshift pros

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

"I found all parts --loading, transformation, processing & querying work in parallel, and end-to-end-- to be valuable."

"Viewpoint, the detailed query logs and performance statistics are valuable features."

"The cloud is ten times better than physical hardware; it is more cost-effective and the upgrade process is ten times easier."

"The solution scales well on the cloud."

"The flexibility in design is very good."

"The solution's banking model, called FSLDM (Financial Services Logical Data Model), is sophisticated and good."

"The key advantages are Performance when processing Terabytes of data and scalability."

More Teradata pros

Cons

"It would be nice if we could turn off an instance. However, it would retain the instance in history, thus allowing us to restart without beginning from scratch."

"If you require a highly scalable solution, I would not recommend Amazon Redshift."

"There are physically too many pipelines for a company of this size to maintain. For a data scientist, it's very difficult to learn the data in all of these different environments."

"There is some missing functionality and sometimes it's so difficult to work in. We need to convert these functionalities using VACUUM inside Amazon Redshift and then it causes some complexity."

"The OLAP slide and dice features need to be improved."

"It would be good to see Redshift as a serverless offering."

"Redshift's GUI could be more user-friendly. It's easier to perform queries and all that stuff in Azure Synapse Analytics."

"Sometimes, it's difficult to get the metadata from Redshift."

More Amazon Redshift cons

"The solution could improve by having a cloud version or a cloud component. We have to use other solutions, such as Amazon AWS, Microsoft Azure, or Snowflake for the cloud."

"The following could be better: licensing, architecture openness, integration with other tools."

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

"Sometimes the large injestion takes days to load data, and some of our stored procedures take two to three days."

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

"There is some improvement required on OLTP level and some analytical function is missing."

"Teradata needs to pay attention to the cloud-based solution to make sure it runs smoothly."

"I would like more security and speed."

More Teradata cons

Pricing and Cost Advice

"The best part about this solution is the cost."

"The cost must be improved."

"Per hour pricing is helpful to keep the costs of a pilot down, but long-term retention is expensive."

"On a scale of one to ten, where one is a low price and ten is a high price, I rate the pricing a seven."

"The solution has very competitive pricing."

"The cost will depend on how you set up your warehouse and what kind of data you store."

"It's pay per use. You can have multiple models."

"My customers have implementations that cost about $500 a month for a very small one. I also have a customer with a monthly invoice of about $25,000 USD."

More Amazon Redshift pricing and cost advice

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

"Teradata is a very expensive solution."

"I am using the free version of Teradata."

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

"It's a very expensive product."

"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."

"Make sure you have the in-house skills to design and support the solution, as relying on external sources is extremely costly and tends to lock you into specific platforms, tools, and paradigms."

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

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

Educational Organization

59%

Financial Services Firm

Computer Software Company

Manufacturing Company

Financial Services Firm

25%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

How does Amazon Redshift compare with Microsoft Azure Synapse Analytics?

Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different dat...

What do you like most about Amazon Redshift?

The tool's most valuable feature is its parallel processing capability. It can handle massive amounts of data, even when pushing hundreds of terabytes, and its scaling capabilities are good.

What is your experience regarding pricing and costs for Amazon Redshift?

You can start small with a basic cluster to learn and practice with it. Selecting the most basic and economical cluster type can save you enough money to move forward with the solution or go with a...

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,...

Oracle Exadata vs Amazon Redshift

Comparisons

Compared 11% of the time

Vertica vs Amazon Redshift

Compared 11% of the time

Snowflake vs Amazon Redshift

Compared 10% of the time

Microsoft Azure Synapse Analytics vs Amazon Redshift

Compared 9% of the time

AWS Lake Formation vs Amazon Redshift

Compared 8% of the time

More Amazon Redshift Competitors

SQL Server vs Teradata

Compared 14% of the time

Oracle Exadata vs Teradata

Compared 13% of the time

Snowflake vs Teradata

Compared 9% of the time

MySQL vs Teradata

Compared 8% of the time

IBM Db2 Database vs Teradata

Compared 5% of the time

More Teradata Competitors

Product Reports

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Amazon Redshift

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September 2024

Also Known As

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

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Amazon Web Services (AWS)

Overview

What is Amazon Redshift?

Amazon Redshift is a fully administered, petabyte-scale cloud-based data warehouse service. Users are able to begin with a minimal amount of gigabytes of data and can easily scale up to a petabyte or more as needed. This will enable them to utilize their own data to develop new intuitions on how to improve business processes and client relations.

Initially, users start to develop a data warehouse by initiating what is called an Amazon Redshift cluster or a set of nodes. Once the cluster has been provisioned, users can seamlessly upload data sets, and then begin to perform data analysis queries. Amazon Redshift delivers super-fast query performance, regardless of size, utilizing the exact SQL-based tools and BI applications that most users are already working with today.

The Amazon Redshift service performs all of the work of setting up, operating, and scaling a data warehouse. These tasks include provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine.

Amazon Redshift Functionalities

Amazon Redshift has many valuable key functionalities. Some of its most useful functionalities include:

Cluster administration: The Amazon Redshift cluster is a group of nodes that contains a leader node and one (or more) compute node(s). The compute nodes needed are dependent on the data size, amount of queries needed, and the query execution functionality desired.
Cluster snapshots: Snapshots are backups of a cluster from an exact point in time. Amazon Redshift offers two types of snapshots: manual and automated. Amazon will store these snapshots internally in the Amazon Simple Storage Service (Amazon S3) utilizing an SSL connection. Whenever a Snapshot restore is needed, Amazon Redshift will create a new cluster and will import data from the snapshot as directed.
Cluster access: Amazon Redshift provides several intuitive features to help define connectivity rules, encrypt data and connections, and control the overall access of your cluster.
IAM credentials and AWS accounts: The Amazon Redshift cluster is only accessible by the AWS account that created the cluster. This automatically secures the cluster and keeps it safe. Inside the AWS account, users access the AWS Identity and IAM protocol to create additional user accounts and manage permissions, granting specified users the desired access needed to control cluster performance.
Encryption: Users have the option to choose to encrypt the clusters for additional added security once the cluster is provisioned. When encryption is enabled, Amazon Redshift will store all the data in user-created tables in a secure encrypted format. To manage Amazon Redshift encryption keys, users will access AWS Key Management Service (AWS KMS).

Reviews from Real Users

“Redshift's versioning and data security are the two most critical features. When migrating into the cloud, it's vital to secure the data. The encryption and security are there.” - Kundan A., Senior Consultant at Dynamic Elements AS

“With the cloud version whenever you want to deploy, you can scale up, and down, and it has a data warehousing capability. Redshift has many features. They have enriched and elaborate documentation that is helpful.”- Aishwarya K., Solution Architect at Capgemini

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

Liberty Mutual Insurance, 4Cite Marketing, BrandVerity, DNA Plc, Sirocco Systems, Gainsight, Blue 449

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