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Snowflake Analytics vs Teradata comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 12, 2025

Review summaries and opinions

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

ROI

Sentiment score
6.4
Users report varied ROI from Snowflake Analytics, with savings in time and cost, yet financial gains need time to evaluate.
Sentiment score
8.1
Teradata boosts analytics speed over 100%, enhancing customer service and satisfaction, with high ROI and user approval.
 

Customer Service

Sentiment score
6.9
Snowflake Analytics' customer service is praised for responsiveness and support, though larger organizations face delays in urgent cases.
Sentiment score
7.1
Teradata's customer service is praised for expertise but criticized for delays, with ratings ranging from 6 to 10 out of 10.
The technical support from Teradata is quite advanced.
Customer support is very good, rated eight out of ten under our essential agreement.
 

Scalability Issues

Sentiment score
8.0
Snowflake Analytics offers scalable, efficient cloud-based data handling with auto-scaling, praised for integration but some cost concerns.
Sentiment score
7.4
Teradata is praised for its scalability, speed, and flexibility, despite some complexity and cost challenges in cloud environments.
Storage is unlimited because they use S3 if it is AWS, so storage has no limit.
This expansion can occur without incurring downtime or taking systems offline.
Scalability is complex as you need to purchase a license and coordinate with Teradata for additional disk space and CPU.
 

Stability Issues

Sentiment score
8.5
Snowflake Analytics is praised for its stability, reliability, and high availability, with minimal outages and strong cloud-based performance.
Sentiment score
8.4
Teradata excels in stability with minimal downtime, robust architecture, 99.9% uptime, and reliable performance, despite minor large dataset issues.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
 

Room For Improvement

Snowflake Analytics requires improved machine learning integration, UI intuitiveness, pricing clarity, and enhanced data management and governance features.
Teradata users seek better transaction processing, enhanced scalability, modern interface, cloud focus, advanced analytics, and improved support and documentation.
AIML-based SQL prompt and query generation could be an area for enhancement.
Navigating the user console can be challenging, particularly when looking for details like the account ID.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
 

Setup Cost

Snowflake Analytics pricing is usage-based, with flexible plans, potentially expensive without optimal configuration, and options for discounts.
Teradata's high cost is justified by its superior performance, competitive total ownership costs, and flexible pricing models.
Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.
Snowflake is better and cheaper than Redshift and other cloud warehousing systems.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
 

Valuable Features

Snowflake Analytics provides scalable, secure data management with advanced features, seamless integration, and compatibility across major cloud platforms.
Teradata offers efficient, scalable data management with fast query performance, robust security, automation, and cloud flexibility for businesses.
Running a considerable query on Microsoft SQL Server may take up to thirty minutes or an hour, while Snowflake executes the same query in less than three minutes.
It is a data offering where I can see data lineage, data governance, and data security.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
 

Categories and Ranking

Snowflake Analytics
Ranking in Cloud Data Warehouse
8th
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
39
Ranking in other categories
Web Analytics (1st)
Teradata
Ranking in Cloud Data Warehouse
6th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
76
Ranking in other categories
Customer Experience Management (4th), Backup and Recovery (20th), Data Integration (16th), Relational Databases Tools (7th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th)
 

Mindshare comparison

As of February 2025, in the Cloud Data Warehouse category, the mindshare of Snowflake Analytics is 0.6%, down from 0.6% compared to the previous year. The mindshare of Teradata is 9.0%, down from 9.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

KamleshPant - PeerSpot reviewer
Data ecosystem thrives with advanced governance and streaming capabilities
It is a data offering where I can see data lineage, data governance, and data security. Snowflake has a streaming capability to work with real-time streaming data and delta tables. Additionally, task management, job scheduling, and connecting multiple data sources unify my data across internal and external sources. The system ecosystem for analytics is enhanced, and AI capabilities are incorporated.
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.
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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
Computer Software Company
17%
Retailer
12%
Financial Services Firm
8%
Manufacturing Company
7%
Financial Services Firm
27%
Computer Software Company
10%
Manufacturing Company
8%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is your experience regarding pricing and costs for Snowflake Analytics?
We don't handle the price part. However, our customer is happy with our services regarding Snowflake Analytics.
What needs improvement with Snowflake Analytics?
When we insert data into a large table, it takes a lot of time. This performance issue can be improved.
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,...
 

Comparisons

 

Also Known As

No data available
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture
 

Overview

 

Sample Customers

Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper
Netflix
Find out what your peers are saying about Snowflake Analytics vs. Teradata and other solutions. Updated: January 2025.
832,723 professionals have used our research since 2012.