Pivotal Greenplum vs. Teradata

As of March 2019, Pivotal Greenplum is ranked 8th in Data Warehouse with 4 reviews vs Teradata which is ranked 2nd in Data Warehouse with 19 reviews. The top reviewer of Pivotal Greenplum writes "Handles complex queries and report production efficiently, integrates with Hadoop". The top reviewer of Teradata writes "It is the core of our fundamental real-time reporting and operational planning. ". Pivotal Greenplum is most compared with Apache Hadoop, Teradata and Vertica. Teradata is most compared with Oracle Exadata, SQL Server and Amazon Redshift. See our Pivotal Greenplum vs. Teradata report.
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Pivotal Greenplum Logo
16,974 views|6,428 comparisons
Teradata Logo
20,764 views|12,162 comparisons
Most Helpful Review
Find out what your peers are saying about Pivotal Greenplum vs. Teradata and other solutions. Updated: March 2019.
325,652 professionals have used our research since 2012.
Quotes From Members

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

Pros
It's one of the fastest databases in the market. It's easy to use. From a maintenance perspective it's a good product. The segmentation, or architecture of the product is different than other databases such as Oracle. So even in 10 years, the data distribution for such segments will not affect other segments. The query performance of the product, for complex queries, is very good. It has good integration with Hadoop.Very fast for query processing.Scalable (Massive) Parallel Processing (MPP) – The ability to bring to bear large amounts of compute against large data sets with Greenplum and the EMC DCA has proven itself to be very effective.

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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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Cons
Implementation takes a long time.One of the disadvantages, not a disadvantage with the product itself, but overall, is the expertise in the marketplace. It's not easy to find a Greenplum administrator in the market, compared to other products such as Oracle.they need to interact more with customers. They need to explain the features, especially when there are new releases of Greenplum. I know just from information I've found that it has other features, it can be used to for analytics, for integration with Big Data, Hadoop. They need to focus on this part with the customer.They need to enhance integration with other Big Data products... to integrate with Big Data platforms, and to open a bi-directional connection between Greenplum and Big Data.It will be very useful if we could communicate with other database types from Greenplum (using a database link).We would like to see Greenplum maintain a closer relationship with and parity to features implemented in PostgreSQL.

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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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Pricing and Cost Advice
Pricing is good compared to other products. It's fine.It is the best product with best fit for price/performance customer objectives.

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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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report
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325,652 professionals have used our research since 2012.
Ranking
8th
out of 30 in Data Warehouse
Views
16,974
Comparisons
6,428
Reviews
4
Followers
399
Avg. Rating
8.3
2nd
out of 30 in Data Warehouse
Views
20,764
Comparisons
12,162
Reviews
19
Followers
860
Avg. Rating
8.5
Top Comparisons
Compared 44% of the time.
Compared 13% of the time.
Compared 12% of the time.
Compared 23% of the time.
Compared 20% of the time.
Compared 7% of the time.
Also Known As
Greenplum
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Pivotal
Teradata
Overview

Advanced analytics meets traditional business intelligence with Pivotal Greenplum, the world’s first fully-featured, multi-cloud, massively parallel processing (MPP) data platform based on the open source Greenplum Database. Pivotal Greenplum provides comprehensive and integrated analytics on multi-structured data. Powered by one of the world’s most advanced cost-based query optimizers, Pivotal Greenplum delivers unmatched analytical query performance on massive volumes of data.

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

Offer
Learn more about Pivotal Greenplum
Learn more about Teradata
Sample Customers
General Electric, Conversant, China CITIC Bank, Aridhia, Purdue UniversityNetflix
Top Industries
REVIEWERS
Financial Services Firm44%
Marketing Services Firm19%
Comms Service Provider19%
Retailer6%
VISITORS READING REVIEWS
Financial Services Firm43%
Comms Service Provider23%
Manufacturing Company5%
Transportation Company5%
VISITORS READING REVIEWS
Financial Services Firm30%
Comms Service Provider22%
Software R&D Company12%
Government8%
Company Size
REVIEWERS
Small Business14%
Midsize Enterprise19%
Large Enterprise67%
VISITORS READING REVIEWS
Small Business30%
Midsize Enterprise30%
Large Enterprise40%
REVIEWERS
Small Business18%
Midsize Enterprise5%
Large Enterprise77%
VISITORS READING REVIEWS
Small Business38%
Midsize Enterprise17%
Large Enterprise46%
Find out what your peers are saying about Pivotal Greenplum vs. Teradata and other solutions. Updated: March 2019.
325,652 professionals have used our research since 2012.
We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.

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