Teradata vs. Vertica

Teradata is ranked 4th in Relational Databases with 19 reviews vs Vertica which is ranked 3rd in Data Warehouse with 15 reviews. The top reviewer of Teradata writes "It is the core of our fundamental real-time reporting and operational planning. ". The top reviewer of Vertica writes "The architecture means it can process/ingest data in parallel to reporting and analyzing because of in-memory Write-Optimized Storage alongside the analytics optimized Read-Optimized Storage". Teradata is most compared with Oracle Exadata, SQL Server and Vertica. Vertica is most compared with Oracle Exadata, Teradata and Pivotal Greenplum. See our Teradata vs. Vertica report.
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Quotes From Members Comparing Teradata vs. Vertica

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Pros
It handles large amounts of information with a linear performance increase, in relation to a HW investment.It has a solid set of tools and consulting services.It has massive parallel processing ability to do large amounts of concurrent querying.It has given our business the ability to gain insights into the data and create data labs for analysis and PoCs.Cuts time to process huge amounts of data with efficient analytical queries.A conventional and easily defined way to build a data warehouse or a layer of data marts.Teradata can be easily used in ETL mode transformations, so there is no need for expensive and inconvenient ETL toolsAuto-partitioning and indexing, and resource allocation on the fly are key features.

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Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data.Allows us to take volumes and process them at a very high speed.Bulk loads, batch loads, and micro-batch loads have made it possible for our organization to process near real-time ingestions and faster analytics.Any novice user can tune vertical queries with minimal training (or no training at all).Vertica gives knowledgeable users and DBAs excellent tools for tuning.Its projections and encoding are excellent tools for tuning large volumes.Its analytics has enabled Pythian's clients to get the business insights as quick as they wanted. Its lower maintenance has also improved the ROI.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.

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Cons
It needs a teaching web site with more training on third-party tools used for BI.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 is a need to improve performance in high transaction processes, as well as the reporting system.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).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.Needs compatibility with more Big Data platforms.It would help to make scaling easier with a reduced cost. ​​I think the UI is not there yet. It could be improved by being more user-friendly.​

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Support is an area where it could get better.Promotion/marketing must be improved, even though it is a very useful product at very good price, it is not as "popular" as it should be.It should provide a GUI interface for data management and tuning.Monitoring tools need to be lightweight. They should not take up heavy resources of the main server.If you do not utilize the tuning tools like projections, encoding, partitions, and statistics, then performance and scalability will suffer.It would be great if this were a managed service in AWS.One feature, which has really benefited us, is the scalability offered by Vertica as it has enabled Pythian's clients to manage data with agility.I believe the installation process could be streamlined.

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Pricing and Cost Advice
We are looking for a more flexible cost model for the next version that we use, whether it be cloud or on-premise.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.Teradata is expensive but gives value for money, especially if you don't want to move your data to the cloud.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.Teradata is currently making improvements in this area.The initial cost may seem high, but the TCO is low.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.Make sure you have the in-house skills to design and support the solution, as relying on external sources is extremely costly and tends to lock you into specific platforms, tools, and paradigms.

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Read the fine print carefully.I think it's starting to get a little expensive. Open source products are starting to get more robust, so I think that's something that they need to start looking at in terms of licensing.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.Start with license per 1TB. Starting from hundreds of TB there is unlimited licensing to be considered. Move historical data to HDFS/S3 which are significantly cheaper or even free.It's free up to three nodes and 1TB, and then get in contact with their sales guys.

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Ranking
Views
18,351
Comparisons
11,407
Reviews
19
Followers
789
Avg. Rating
8.5
Views
24,975
Comparisons
7,633
Reviews
15
Followers
744
Avg. Rating
8.6
Unranked
In Relational Databases
Top Comparisons
Compared 28% of the time.
Compared 17% of the time.
Compared 11% of the time.
See more Teradata competitors »
Compared 18% of the time.
Compared 16% of the time.
Compared 12% of the time.
See more Vertica competitors »
Compared 29% of the time.
Also Known As
Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand
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Teradata
Micro Focus
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Overview

Teradata's portfolio of big data analytic solutions, integrated marketing applications, and services help organizations gain a sustainable competitive advantage with data.

Micro Focus Vertica is the most advanced SQL database analytics portfolio built from the very first line of code to address the most demanding Big Data analytics initiatives. Micro Focus Vertica delivers speed without compromise, scale without limits, and the broadest range of consumption models. Choose Vertica on premise, on demand, in the cloud, or on Hadoop. With support for all leading BI and visualization tools, open source technologies like Hadoop and R, and built-in analytical functions, Vertica helps you derive more value from your Enterprise Data Warehouse and data lakes and get to market faster with your analytics initiatives.

To learn more about Micro Focus Vertica Advanced Analytics, visit our website.

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Sample Customers
NetflixCerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.
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Top Industries
VISITORS READING REVIEWS
Financial Services Firm
28%
Comms Service Provider
16%
Energy/Utilities Company
6%
Software R&D Company
5%
REVIEWERS
Media Company
21%
Software R&D Company
21%
Marketing Services Firm
17%
Comms Service Provider
14%
VISITORS READING REVIEWS
Financial Services Firm
21%
Comms Service Provider
19%
Marketing Services Firm
9%
Media Company
9%
No Data Available
Company Size
REVIEWERS
Small Business
18%
Midsize Enterprise
5%
Large Enterprise
77%
VISITORS READING REVIEWS
Small Business
24%
Midsize Enterprise
14%
Large Enterprise
62%
REVIEWERS
Small Business
29%
Midsize Enterprise
24%
Large Enterprise
47%
VISITORS READING REVIEWS
Small Business
23%
Midsize Enterprise
25%
Large Enterprise
52%
No Data Available
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