Teradata vs Vertica comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Teradata
Ranking in Data Warehouse
3rd
Average Rating
8.2
Number of Reviews
56
Ranking in other categories
Relational Databases Tools (7th)
Vertica
Ranking in Data Warehouse
4th
Average Rating
8.2
Number of Reviews
85
Ranking in other categories
Cloud Data Warehouse (6th)
 

Mindshare comparison

As of July 2024, in the Data Warehouse category, the mindshare of Teradata is 15.2%, up from 14.1% compared to the previous year. The mindshare of Vertica is 9.8%, up from 8.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Warehouse
Unique Categories:
Relational Databases Tools
5.7%
Cloud Data Warehouse
4.4%
 

Featured Reviews

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.
SR
Mar 20, 2023
Reliable and feature-rich, with optimization techniques to fine-tune queries for faster report generation
In my opinion, Vertica's documentation could be improved. Currently, there is not enough documentation available to gain a comprehensive understanding of the platform. Additionally, the community support for Vertica is limited, making it difficult to find assistance or resources when needed. When it comes to data sharing or desktop usage, Snowflake has an advantage over Vertica and other platforms such as cash. Snowflake provides reporting capabilities to share data between two different accounts, which is not currently available in Vertica. This feature is particularly helpful when sharing data with third-party vendors or clients. However, Vertica does not provide such capabilities, and it is not possible to set up data sharing between two different accounts with just a few clicks, as it is possible in Snowflake.

Quotes from Members

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

Pros

"The two types of partitioning have been very significant for us - row and columnar partitioning."
"Teradata's pretty fast."
"Things have started moving faster in my company, such as data retrieval happens more quickly.​"
"Cuts time to process huge amounts of data with efficient analytical queries."
"Teradata's capabilities enhance data management efficiency, support scalability, and contribute to faster query performance."
"The key advantages are Performance when processing Terabytes of data and scalability."
"It is a stable solution. Stability-wise, I rate the solution a nine out of ten."
"The solution scales well on the cloud."
"Vertica uses advanced Azure technologies to compress raw data using indexing, allowing a large amount of data to be stored with minimal physical space. Advanced algorithms are employed in data compression."
"The feature I like best is performance. We use Red Tool and Red Job for the data warehouse and reporting. It's perfect. Performance is good, and it can return ad hoc queries very quickly. Of course, it's a cluster, so it's easy to scale."
"Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data."
"Bulk loads, batch loads, and micro-batch loads have made it possible for our organization to process near real-time ingestions and faster analytics."
"The feature of the product that is most important is the speed. I needed a columnar database, and its speed is what it's built to do, and so that's what really does differentiate Vertica from its competitors."
"Initiate on one node, and the RPM propagates automatically to all other nodes. ​"
"The Vertica architecture means it can process/ingest data in parallel to reporting and analyzing because of its in-memory Write-Optimized Storage sitting alongside the analytics optimized Read-Optimized Storage."
"For me, It's performance, scalability, low cost, and it's integrated into enterprise and big data environments."
 

Cons

"The solution could improve by having a cloud version or a cloud component. We have to use other solutions, such as Amazon AWS, Microsoft Azure, or Snowflake for the cloud."
"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."
"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."
"Teradata needs to expand the kind of training that's available to customers. Teradata only offers training directly and doesn't delegate to any third-party companies. As a result, it's harder to find people trained on Teradata in our market relative to Oracle."
"GUI of administrative tools is really outdated."
"The tool's flexibility and capacity for expansion are areas of concern where improvements are required."
"The solution is stable. However, there are times when we are using large amounts of data and we can see some latency issues."
"​I think the UI is not there yet. It could be improved by being more user-friendly.​"
"Metadata for database files scale okay, but metadata related to tables/columns/sequences must be stored on all nodes."
"The integration of this solution with ODI could be improved."
"If you do not utilize the tuning tools like projections, encoding, partitions, and statistics, then performance and scalability will suffer."
"I believe the installation process could be streamlined."
"In my opinion, Vertica's documentation could be improved. Currently, there is not enough documentation available to gain a comprehensive understanding of the platform."
"When it is about to reach the maximum storage capacity, it becomes slow."
"Performance of management of metadata layer (database catalog) needs improvement. We still have to have smaller customers on PostgreSQL; Vertica cannot manage thousands of schemata."
"It would be great if this were a managed service in AWS."
 

Pricing and Cost Advice

"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."
"The price needs to be more competitive as Hadoop, Redshift, Snowflake, etc are constantly making way into EDW space."
"Teradata is a very expensive solution."
"It comes at a notably high cost for what it offers."
"The solution requires a license."
"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."
"Teradata is currently making improvements in this area."
"The price of the solution could be reduced, it is expensive."
"It is fast to purchase through the AWS Marketplace."
"The pricing and licensing depend on the size of your environment and the zone where you want to implement."
"Read the fine print carefully."
"It's free up to three nodes and 1TB, and then get in contact with their sales guys."
"From a cost perspective, the software is less than most of its competitors."
"The pricing could improve, it is a little expensive."
"It's difficult today to compete with open-source solutions. In these areas, there is a lot of competition and the price of this solution is a bit pricy."
"The first TB is free and you can use all the Vertica features. After 1TB you have to pay for licensing. The product is worth it, but be aware of this condition, and plan. The compression ratio is explained in the documentation."
report
Use our free recommendation engine to learn which Data Warehouse solutions are best for your needs.
792,694 professionals have used our research since 2012.
 

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
26%
Computer Software Company
10%
Manufacturing Company
8%
Healthcare Company
7%
Financial Services Firm
17%
Computer Software Company
17%
Manufacturing Company
9%
University
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

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,...
What do you like most about Vertica?
Vertica is easy to use and provides really high performance, stability, and scalability.
What is your experience regarding pricing and costs for Vertica?
I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.
What needs improvement with Vertica?
Pricing could be more competitive.
 

Comparisons

 

Also Known As

No data available
Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand
 

Learn More

 

Overview

 

Sample Customers

Netflix
Cerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.
Find out what your peers are saying about Teradata vs. Vertica and other solutions. Updated: July 2024.
792,694 professionals have used our research since 2012.