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Alteryx vs Anaconda vs Teradata comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Mindshare comparison

Predictive Analytics
Data Science Platforms
Data Warehouse
 

Featured Reviews

Theresa McLaughlin - PeerSpot reviewer
Quick development enables seamless data processing despite occasional support issues
There were times when the product would fail during development without an apparent reason. The support structure changed; initially, we received great support, however, it later became less reliable due to licensing issues and a tiered support system. Licensing negotiations were problematic, affecting our product usage. For instance, our licenses were temporarily lost during negotiations when an agreement couldn't be reached.
Rohan Sharma - PeerSpot reviewer
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.
SurjitChoudhury - PeerSpot reviewer
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.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Alteryx has helped us spend more time identifying results instead of performing analysis manually. It has helped us in our loading process, including scrubbing data and identifying data elements that need to be corrected. It enables us to understand our data sets a lot better."
"Alteryx is a low-code platform, and that's the biggest reason why we chose it."
"The most valuable feature of Alteryx is the intelligence suite."
"The modeling features are very good."
"I believe that the ability to leverage the gallery for scalability, as well as the general data blending functionality, is most beneficial to our core-based users."
"The solution has been stable."
"The cloud deployment ensures it scales easily."
"It helps clean messy data and provides spatial analysis."
"The most advantageous feature is the logic building."
"The solution is stable."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"Anaconda is an open-source platform that can integrate numerous other kits and models in one place."
"The notebook feature is an improvement over RStudio."
"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."
"I can use Anaconda for non-heavy tasks."
"The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"The two types of partitioning have been very significant for us - row and columnar partitioning."
"In Data Lab, you can schedule any testing you want to do in production. You can take a small subset of data from production, copy it there, and run all your tests. It reduces your testing costs because it's all in the lab."
"The key advantages are Performance when processing Terabytes of data and scalability."
"Teradata's most valuable feature is that it's easy to use."
"The functionality of the solution is excellent."
"It is a highly robust software solution."
"Intelliflex is very scalable. In fact, scalability has improved 100 times by Intelliflex, in my personal opinion."
"The most valuable feature is the ease of running queries."
 

Cons

"The pricing seems high for my current needs. However, considering the benefits, it is easier to justify to management for broader company usage."
"The next feature release should include easier reporting."
"When configuring target tables, it is difficult to see the full text when deciding on load operations."
"The data integration component could most likely be improved to increase enterprise scalability."
"It would be great if Alteryx could take third party tools and incorporate them."
"The product could benefit from improved integration with visualization tools or even the inclusion of built-in visualization features."
"The only area where the product lags is documentation and videos on the analytical app and the batch macro."
"We are hoping that the NLP features will also support Chinese characters."
"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."
"Anaconda should be optimized for RAM consumption."
"The process could be streamlined as the number of actions needed to deploy is quite large compared to other tools."
"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 could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"Anaconda consumes a significant amount of processing memory when working on it."
"Data ingestion is done via external utilities and not by the query language itself. It would be more convenient to have that functionality within its SQL dialect."
"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."
"Teradata needs to pay attention to the cloud-based solution to make sure it runs smoothly."
"Teradata is a bit late for the cloud."
"It is hard for some of our users to set up rules for cleansing and transforming data, so this is something that could be improved."
"Sometimes the large injestion takes days to load data, and some of our stored procedures take two to three days."
"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."
"There are some ways that the handling of unstructured data could be improved."
 

Pricing and Cost Advice

"I rate the tool's pricing a two out of ten."
"The designer has a list price of $5,995 USD."
"I don't know much about the licensing, but there are some additional costs for certain features."
"In order to have designers, and, if you want to collaborate, you have to buy a server. If the designer is $5,000, and if you want a server, you have to pay $80,000."
"The solution has a more costly license than other tools in the market."
"Alteryx is an expensive solution."
"The price for Alteryx Designer is reasonable but the price for Alteryx Server for universal collaborations is too expensive."
"There is a license required for this solution."
"The licensing costs for Anaconda are reasonable."
"Anaconda is free to use, but in terms of hardware costs, you might need heavy GPUs to run CUDA and other demanding tasks."
"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."
"The price of the solution could be reduced, it is expensive."
"The price needs to be more competitive as Hadoop, Redshift, Snowflake, etc are constantly making way into EDW space."
"The cost is substantial, totaling around $1.2 million, solely dedicated to upgrading the hardware."
"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."
"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."
"The cost of running Teradata is quite high, but you get a good return on investment."
"The product cost is high for what the client gets. There may be more cost-effective solutions for small and medium-sized organizations."
"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."
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Comparison Review

it_user232068 - PeerSpot reviewer
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…
 

Top Industries

By visitors reading reviews
Financial Services Firm
24%
Manufacturing Company
9%
Computer Software Company
9%
Healthcare Company
6%
Financial Services Firm
20%
Computer Software Company
9%
Manufacturing Company
8%
Government
8%
Financial Services Firm
26%
Computer Software Company
11%
Manufacturing Company
7%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
One of the differences is that with Alteryx you can use it as an ETL and analytics tool. Please connect with me direc...
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
Alteryx is an extremely easy and flexible data tool, flexible in terms of drag and drop toolset and also has python, ...
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
I am not familiar with IBM SPSS Modeler, therefore, I cannot compare these two products. Regarding Alteryx I can say...
What do you like most about Anaconda?
The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using...
What is your experience regarding pricing and costs for Anaconda?
Anaconda does not require a pricing structure, and it is available as an open-source tool. The features of Python, Ju...
What needs improvement with Anaconda?
Anaconda consumes a significant amount of processing memory when working on it. This is something that needs improvem...
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 d...
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 ...
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 ...
 

Comparisons

 

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Overview

 

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen
LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
Netflix
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