Anaconda vs Teradata comparison

The compared Anaconda and Teradata solutions aren't in the same category. Anaconda is ranked #12 in Data Science Platforms , with an average rating of 8.7, and holds a 2.1% mindshare in the category. Teradata is ranked #3 in Data Warehouse , with an average rating of 7.5, and holds a 15.9% mindshare. Additionally, 95% of Anaconda users are willing to recommend the solution, compared to 87% of Teradata users who would recommend it.

Anaconda

Read 19 Anaconda reviews

1,375 Views
1,124 Comparison Views

95% willing to recommend

Teradata

Read 76 Teradata reviews

3,838 Views
2,879 Comparison Views

87% willing to recommend

Anaconda

Teradata

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Executive Summary

We performed a comparison between Anaconda and Teradata based on real PeerSpot user reviews.

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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

Anaconda

Average Rating

8.2

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Data Science Platforms (12th)

Teradata

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), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Anaconda is designed for Data Science Platforms and holds a mindshare of 2.1%, up 2.1% compared to last year.
Teradata, on the other hand, focuses on Data Warehouse, holds 15.9% mindshare, up 15.5% since last year.

Data Science Platforms

Data Warehouse

Featured Reviews

Rohan Sharma

AI/ML Co-Lead at Developer Student Clubs - GGV

Provides all the frameworks and makes it easy to create environments for multiple projects

The best thing is that it provides all the frameworks and makes it easy to create environments for multiple projects using Anaconda. It is easy for a beginner to learn to use Anaconda. Comparatively, it is easier than using virtual environments or other environments because of the Conda environment. However, there are many things in Anaconda that people need to be aware of, so it can be challenging.

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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 advantageous feature is the logic building."

"The notebook feature is an improvement over RStudio."

"With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages."

"It's interesting. It's user friendly. That's what makes it outstanding among the others. It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science."

"The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."

"The most valuable feature is the Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results."

"The solution is stable."

"I can use Anaconda for non-heavy tasks."

More Anaconda pros

"The solution scales well on the cloud."

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

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

"Auto-partitioning and indexing, and resource allocation on the fly are key features."

"Teradata features high productivity and reliability because it has several redundancy options, so the system is always up and running."

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

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

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

More Teradata pros

Cons

"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."

"Anaconda should be optimized for RAM consumption."

"One feature that I would like to see is being able to use a different language in a different cell, which would allow me to mix R and Python together."

"It also takes up a lot of space."

"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."

"The interface could be improved. Other solutions, like Visual Studio, have much better UI."

"Having a small guide or video on the tool would help learn how to use it and what the features are."

"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."

More Anaconda cons

"I think the UI is not there yet. It could be improved by being more user-friendly."

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

"Teradata could improve by being less complicated. There are some aspects that are not available on the Unix server and a Unix system is required to access some data, such as in case of an emergency."

"Query language and its functionality are rather limited, compared to Oracle or even SQL Server. However, it is possible to perform any kind of logic in it (though some workarounds may be required)."

"Their level of technical support is adequate. It could be better."

"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."

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

"The current operational approach needs improvement."

More Teradata cons

Pricing and Cost Advice

"The licensing costs for Anaconda are reasonable."

"The product is open-source and free to use."

"My company uses the free version of the tool. There is also a paid version of the tool available."

"The tool is open-source."

"Anaconda is free to use, but in terms of hardware costs, you might need heavy GPUs to run CUDA and other demanding tasks."

"Teradata is expensive but gives value for money, especially if you don't want to move your data to the cloud."

"It comes at a notably high cost for what it offers."

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

"The cost is significantly high."

"Teradata is a very expensive solution."

"It's a very expensive product."

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

"It is still a very expensive solution. While I very much like the pure technological supremacy of the software itself, I believe Teradata as a company needs to become more affordable. They are already losing the market to more flexible or cheaper competitors."

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

20%

Computer Software Company

Government

Manufacturing Company

Financial Services Firm

26%

Computer Software Company

11%

Healthcare Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Anaconda?

The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors.

See all answers

What is your experience regarding pricing and costs for Anaconda?

Anaconda is an open-source tool, so I do not pay anything for it. It is compatible with every tool, regardless of whether it is open source or a paid package.

See all answers

What needs improvement with Anaconda?

There is room for improvement, especially regarding deployment. The process could be streamlined as the number of actions needed to deploy is quite large compared to other tools.

See all answers

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...

See all answers

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...

See all answers

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,...

See all answers

Comparisons

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Amazon SageMaker vs Anaconda

Compared 12% of the time

Microsoft Power BI vs Anaconda

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs Anaconda

Compared 7% of the time

IBM SPSS Statistics vs Anaconda

Compared 5% of the time

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Oracle Exadata vs Teradata

Compared 13% of the time

SQL Server vs Teradata

Compared 11% of the time

Snowflake vs Teradata

Compared 7% of the time

MySQL vs Teradata

Compared 6% of the time

IBM Db2 Database vs Teradata

Compared 6% of the time

More Teradata Competitors

Product Reports

Buyer's Guide

Anaconda

May 2025

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Buyer's Guide

Teradata

April 2025

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Also Known As

No data available

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

Overview

Anaconda makes it easy for you to install and maintain Python environments. Our development team tests to ensure compatibility of Python packages in Anaconda. We support and provide open source assurance for packages in Anaconda to mitigate your risk in using open source and meet your regulatory compliance requirements.

Python is the fastest growing language for data science. Anaconda includes 720+ Python open source packages and now includes essential R packages. This powerful combination allows you to do everything you want from BI to advanced modeling on complex Big Data

Anaconda

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

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone

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