Mode Analytics vs Teradata comparison

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394 Comparison Views

87% willing to recommend

Mode Analytics

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Executive SummaryUpdated on Jan 12, 2025

Teradata and Mode Analytics compete in the data analytics platform category. Teradata seems to have the upper hand in supporting large enterprises due to its advanced data warehousing capabilities.

Features: Teradata offers advanced data warehousing, seamless integration with various data sources, and high-performance analytics capabilities. Mode Analytics provides intuitive data exploration, real-time collaboration, and ease of use for interactive data tasks.

Room for Improvement: Teradata can improve by reducing complexity in setup and supporting faster deployment times. Enhancements in user interface design could make it more user-friendly. Mode Analytics could benefit from expanding integration capabilities and optimizing performance for handling large data sets. Improving analytics power to match enterprise needs could also be advantageous.

Ease of Deployment and Customer Service: Teradata provides extensive deployment options, supporting a broad range of business needs, though it may involve lengthy setup processes. Mode Analytics offers simpler deployment models that are quicker to implement, with responsive customer service aiding smooth onboarding.

Pricing and ROI: Teradata's higher initial costs accompany its extensive system needs, potentially yielding substantial ROI for large-scale operations. Mode Analytics offers lower entry costs with rapid ROI focused on flexibility, benefiting smaller teams or cost-conscious businesses.

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

Mode Analytics 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

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 (7th), Data Warehouse (3rd), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of April 2025, in the BI (Business Intelligence) Tools category, the mindshare of Mode Analytics is 0.4%, 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 tool helps to catch results and review them."

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

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

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

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

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

"Teradata's best feature is its speed with historical data."

"It has a solid set of tools and consulting services."

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

"It has reduced a lot of reworking on maintaining indexes, partitions, etc."

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."

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

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

"The solution could run faster."

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

"When backups are performed, it locks the database, preventing user access, which is a concern."

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

"We tried to use case Teradata for a data warehouse system, but we had some problems in relation to the Teradata system, CDC tools, and source databases. We were unable to transfer data from HPE Integrity mainframe to Teradata."

"Needs compatibility with more Big Data platforms."

"Teradata is somewhat late in adopting cloud technology."

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

"GUI of administrative tools is really outdated."

More Teradata cons

Pricing and Cost Advice

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

"Mode Analytics is cheap compared to other tools."

"The pricing is per user."

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

"I rate the product price a nine on a scale of one to ten, where one is cheap and ten is expensive."

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

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

"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."

"The price of Teradata is expensive. However, what they deliver they are outstanding. If you're looking for an inexpensive solution to run a database, this isn't your tool. It's the Ferrari of databases for data warehousing."

"The cost of running Teradata is quite high, but you get a good return on investment."

"Teradata is not cheap, but you get what you pay for."

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%

Financial Services Firm

11%

Manufacturing Company

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 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

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Tableau vs Mode Analytics

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Amazon QuickSight vs Mode Analytics

Compared 14% 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 7% of the time

Snowflake vs Teradata

Compared 7% of the time

IBM Db2 Database vs Teradata

Compared 7% of the time

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Product Reports

BI (Business Intelligence) Tools

March 2025

Download Mode Analytics product report

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March 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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