Actian Ingres vs Teradata comparison

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Actian Ingres

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Executive SummaryUpdated on Jan 12, 2025

Teradata and Actian Ingres are both data management solutions competing in the data integration and analytics market. Teradata has the upper hand in scalability and analytics performance, while Actian Ingres is preferred for its cost-effectiveness and integration capabilities.

Features: Teradata handles large data warehouses, supports advanced analytics, and manages complex queries, making it suitable for businesses needing high data processing power. Actian Ingres provides efficient integration for varied data types, is simple in executing transactional operations, and emphasizes integration flexibility.

Ease of Deployment and Customer Service: Teradata involves a complex deployment process due to its vast framework but offers comprehensive support for onboarding. Actian Ingres is known for its straightforward deployment approach, minimizing initial setup hurdles, complemented by adequate but less extensive customer support options.

Pricing and ROI: Teradata includes a higher initial setup cost, aligning with its enterprise-level capabilities, offering substantial ROI for businesses utilizing its full potential. Actian Ingres presents a lower-cost alternative, providing significant ROI in environments where transaction speed and data integration are priorities.

To learn more, read our detailed Actian Ingres vs. Teradata Report (Updated: January 2025).

Actian Ingres vs. Teradata

January 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

Actian Ingres

Ranking in Data Warehouse

16th

Average Rating

8.6

Reviews Sentiment

7.9

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 (4th), 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 February 2025, in the Data Warehouse category, the mindshare of Actian Ingres is 0.7%, up from 0.6% compared to the previous year. The mindshare of Teradata is 16.1%, up from 15.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse

Featured Reviews

GustavHoltzhausen

Sr Sales Engineer at HCLSoftware

Reliable performance enhances operations with good technical support

We run the entire IRS system, the income system, and the tax system. We also manage the entire Absa banking system in Africa. There's a lot of database applications, similar to those used in banks and the IRS The most valuable features for us are reliability and performance. Our system is used…

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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 features for us are reliability and performance."

"The deployment of our solution across a number of servers using Ingres .NET has meant that we can protect the database server behind a highly secure firewall and deploy the front end solutions on a normal web server."

"I've never had any issues with scalability."

"The ease of deployment is useful so clients are up and running quickly in comparison to other products."

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

"It has increased the speed of reporting."

"The most valuable features are the Shared-nothing architecture and data protection functionality."

"It's a pre-configured appliance that requires very little in terms of setting-up."

"The most valuable features of Teradata are that it is a massively parallel platform and I can receive a lot of data and get the queries out correctly, especially if it's been appropriately designed. The native features make it very suitable for multiple large data tasks in a structured data environment. Additionally, the automation is very good."

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

More Teradata pros

Cons

"The ability to reset the log file without stopping the DBMS would be helpful for us."

"The seamless integration is a bit of an issue."

"The solution’s pricing, scalability, and technical support response time could be improved."

"It would help to make scaling easier with a reduced cost. "

"The tool's flexibility and capacity for expansion are areas of concern where improvements are required."

"Teradata has a few AI models, but in data science, we need more flexibility."

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

"The scalability could be better. The on-premises solution is always more complicated to scale."

"I would like more security and speed."

"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."

More Teradata cons

Pricing and Cost Advice

Information not available

"The price of Teradata could be less expensive."

"Teradata is a very expensive solution."

"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 is currently making improvements in this area."

"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."

"It's a very expensive product."

"We are looking for a more flexible cost model for the next version that we use, whether it be cloud or on-premise."

"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…

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Top Industries

By visitors reading reviews

Computer Software Company

20%

Government

12%

Manufacturing Company

11%

Educational Organization

Financial Services Firm

26%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What needs improvement with Actian Ingres?

The seamless integration is a bit of an issue. I would like to see more direct connectors and stuff like SQLAlchemy. It's there but isn't available as a standard, so it involves going to GitHub to ...

What is your primary use case for Actian Ingres?

What is your experience regarding pricing and costs for Actian Ingres?

Initially, it's a lot less expensive than competitors. Price performance has always been a priority, ensuring we remain competitive in the market.

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 Database Appliance vs Actian Ingres

Comparisons

Compared 100% of the time

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Oracle Exadata vs Teradata

Compared 14% of the time

SQL Server vs Teradata

Compared 11% of the time

MySQL vs Teradata

Compared 8% of the time

Snowflake vs Teradata

Compared 7% of the time

IBM Db2 Database vs Teradata

Compared 6% of the time

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Product Reports

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Data Warehouse

February 2025

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January 2025

Also Known As

Ingres, Ingres 2006

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

Overview

Actian’s Ingres is a leading, enterprise-grade database management system designed to reduce IT costs and time-to-value, while delivering the strength and features expected from an enterprise-class database. Ingres 10.2 is the latest version of the database, containing enhancements that will make it easier to internationalize customer applications. Along with improved performance and reduced configuration overhead, users can take their first steps into big data analytics with the new Window functions.

Actian

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

Groupe Adeo, IsCool Entertainment

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