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Oracle DataScience.com Platform vs Teradata comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Average Rating
8.0
Number of Reviews
36
Ranking in other categories
Data Mining (3rd), Data Science Platforms (10th)
Oracle DataScience.com Plat...
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
Data Science Platforms (31st)
Teradata
Average Rating
8.2
Number of Reviews
74
Ranking in other categories
Customer Experience Management (3rd), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)
 

Mindshare comparison

Data Science Platforms
Data Warehouse
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Sep 21, 2023
Enhancing survey analysis that provides valued insightfulness
I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…
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SurjitChoudhury - PeerSpot reviewer
Feb 20, 2024
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:
 

Pricing and Cost Advice

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"We think that IBM SPSS is expensive for this function."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."
"I rate the tool's pricing a five out of ten."
"The price of this solution is a little bit high, which was a problem for my company."
Information not available
"The tool costs about 30,000 euros a month, while Azure Synapse SQL only costs 10,000."
"In this day and age, we want to get things done quickly. So, we go to the AWS Marketplace."
"The cost is substantial, totaling around $1.2 million, solely dedicated to upgrading the hardware."
"It comes at a notably high cost for what it offers."
"I am using the free version of Teradata."
"The price of Teradata is on the higher side, and I think that it where they lose out on some of their business."
"Teradata is not cheap, but you get what you pay for."
"The price of Teradata could be less expensive."
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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
16%
University
10%
Computer Software Company
9%
Educational Organization
8%
No data available
Financial Services Firm
25%
Computer Software Company
11%
Manufacturing Company
8%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
While the pricing of the product may be higher, the accompanying service and features justify the investment. However...
What needs improvement with IBM SPSS Statistics?
In some cases, the product takes time to load a large dataset. They could improve this particular area.
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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 ...
 

Also Known As

SPSS Statistics
Oracle Data Science Platform, DataScience.com Platform, DataScience, DataScience.com
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture
 

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Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
Sonos, Just Fab, Tradesy, Belkin, DogVacay, Scopely, Topix, Home Chef, Pluto
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