Mode Analytics vs Teradata comparison

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384 Comparison Views

87% willing to recommend

Mode Analytics

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Executive SummaryUpdated on Apr 20, 2025

Teradata and Mode Analytics compete in the analytics and data management category. Teradata seems to have the upper hand due to its extensive capabilities and robust data integration, while Mode Analytics is preferred for its dynamic visualizations.

Features: Teradata offers powerful data processing capabilities that are ideal for large-scale datasets, high concurrency, and enterprise-level data warehousing. Mode Analytics, however, is equipped with user-friendly reporting tools and advanced visualizations, promoting agile analysis and quick decision-making.

Room for Improvement: While Teradata excels in data management, it requires significant resources for setup and might improve by simplifying integration processes. Enhancing user-friendliness could be beneficial. Mode Analytics could improve on data integration capabilities, scalability, and providing more support for larger datasets.

Ease of Deployment and Customer Service: Mode Analytics provides a straightforward cloud-based deployment that is quick and user-friendly. Teradata, known for its complex setup, offers strong support but requires more resources and time for deployment.

Pricing and ROI: Teradata involves higher setup costs due to its extensive capabilities, promising substantial ROI for large-scale operations. Mode Analytics, with cost-effective pricing and rapid implementation, offers strong ROI especially for smaller teams seeking agile, visual-driven analytics.

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

Mode Analytics vs. Teradata

April 2025

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Helped 851,451 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:

Categories and Ranking

Mode Analytics

Ranking in BI (Business Intelligence) Tools

24th

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in BI (Business Intelligence) Tools

10th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (8th), Data Warehouse (3rd), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of May 2025, in the BI (Business Intelligence) Tools category, the mindshare of Mode Analytics is 0.5%, up from 0.3% compared to the previous year. The mindshare of Teradata is 0.8%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

BI (Business Intelligence) Tools

Featured Reviews

Yoeri Samwel

Logistical engineer at DSV

Helps to run Python-based scripts but needs enhancement in user experience

The most important feature of the solution is the ability to run Python-based scripts. Mode Analytics needs to improve the overall user experience. I have been working with the solution for two years. I rate the solution's stability a ten out of ten. I rate the tool's scalability a seven…

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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 solution is simple for people from a viewing perspective, not a coding perspective."

"The most important feature of the solution is the ability to run Python-based scripts."

"The most valuable feature I would say is the flexibility in editing."

"The tool helps to catch results and review them."

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

"Designing the database is easy."

"The most valuable feature is the ease of uploading data from multiple sources."

"We really enjoy the FastLoad, TPump, and MultiLoad features."

"The two types of partitioning have been very significant for us - row and columnar partitioning."

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

"The product is reliable."

"The data processing, clustering, and distributed computing are impressive."

More Teradata pros

Cons

"The data visualization is cumbersome in Mode Analytics. I want the solution to add a map that has an easy interface. The UI is slow sometimes."

"The solution could run faster."

"I think in terms of User Interface, I would say it can be better."

"Mode Analytics needs to improve the overall user experience."

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

"There is a need to improve performance in high transaction processes, as well as the reporting system."

"The initial setup is complex because there are a lot of factors that come into play, including the amount of software and applications that require access."

"The setup is not straightforward."

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

"The solution is stable. However, there are times when we are using large amounts of data and we can see some latency issues."

"From my perspective, it would be good if they gave better ITIN/R plugins to use the data for AI modeling, or data science modeling. We can do it now; however, it could be more elegant in terms of interfacing."

"I would like more security and speed."

More Teradata cons

Pricing and Cost Advice

"Mode Analytics is cheap compared to other tools."

"My decision-maker found the pricing expensive, but it is okay for me."

"The pricing is per user."

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

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

"Teradata's licensing is on the expensive side."

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

"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 initial cost may seem high, but the TCO is low."

"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."

"Teradata is currently making improvements in this area."

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

24%

Media Company

13%

Manufacturing Company

10%

Financial Services Firm

10%

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

What do you like most about Mode Analytics?

The solution is simple for people from a viewing perspective, not a coding perspective.

What needs improvement with Mode Analytics?

The solution could run faster. You just sit there, waiting during the load times, especially for the large ones. And if you're doing a presentation, no one likes awkwardly waiting for it to load. L...

What is your primary use case for Mode Analytics?

I was put in charge of creating a lot of the dashboards, so it was very much that there weren't people at the company that knew how to use the solution. I was just handed the solution when I transf...

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,...

Databricks vs Mode Analytics

Comparisons

Compared 39% of the time

Metabase vs Mode Analytics

Compared 23% of the time

Tableau vs Mode Analytics

Compared 15% of the time

Amazon QuickSight vs Mode Analytics

Compared 12% of the time

Microsoft Power BI vs Mode Analytics

Compared 10% of the time

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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

BI (Business Intelligence) Tools

May 2025

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Download Teradata product report

April 2025

Also Known As

No data available

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

Overview

Mode builds technology that helps analysts and data scientists unlock the value in data. The collaborative analytics platform tightly integrates SQL queries, Python notebooks, and reporting tools to make a profound impact on an entire organization's ability to use data effectively. Mode drives data-informed decisions at innovative companies including Clover Health, Thumbtack, Twitch, and Zenefits. Mode also supports the analytics community with free learning resources, open source SQL queries, and offers its tools for free to anyone analyzing public data.

Mode

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

Lyft, Zenefits, Twitch, Trello, Clover, Grovo, CrowdFlower, Segment, Everlane, Pocket, Highfive

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