Compare Apache Hadoop vs. Teradata

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Apache Hadoop Logo
12,184 views|10,135 comparisons
Teradata Logo
20,989 views|15,261 comparisons
Most Helpful Review
Find out what your peers are saying about Apache Hadoop vs. Teradata and other solutions. Updated: January 2021.
457,459 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
"The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics.""The best thing about this solution is that it is very powerful and very cheap.""What comes with the standard setup is what we mostly use, but Ambari is the most important.""The ability to add multiple nodes without any restriction is the solution's most valuable aspect.""It's good for storing historical data and handling analytics on a huge amount of data.""The most valuable feature is the database.""The most valuable features are powerful tools for ingestion, as data is in multiple systems.""The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."

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"The feature that we find most valuable is its ability to perform Massive Parallel Processing.""The most valuable features are the Shared-nothing architecture and data protection functionality.""It is a stable program.""The functionality of the solution is excellent.""It's a pre-configured appliance that requires very little in terms of setting-up."

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Cons
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it.""The upgrade path should be improved because it is not as easy as it should be.""In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency.""There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution.""The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment.""It would be good to have more advanced analytics tools.""It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake.""The solution needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning."

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"I would like to see an improved Knowledge Base on the web.""The user interface needs to be improved.""An additional feature I would you like to see included in the next release, is that it needs to be more cloud-friendly.""I'm not sure about the unstructured data management capabilities. It could be improved.""It could use some more advanced analytics relating to structured and semi-structured data."

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Pricing and Cost Advice
"This is a low cost and powerful solution."

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"The price needs to be more competitive as Hadoop, Redshift, Snowflake, etc are constantly making way into EDW space."

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Questions from the Community
Top Answer: Apache Hadoop is for data lake use cases. But getting data out of Hadoop for meaningful analytics is indeed need quite an amount of work. by either using spark/Hive/presto and so on. The way i look at… more »
Top Answer: SQreamDB is a GPU DB. It is not suitable for real-time oltp of course. Cassandra is best suited for OLTP database use cases, when you need a scalable database (instead of SQL server, Postgres)… more »
Top Answer: The most valuable features are powerful tools for ingestion, as data is in multiple systems.
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Ranking
3rd
out of 30 in Data Warehouse
Views
12,184
Comparisons
10,135
Reviews
10
Average Words per Review
426
Rating
7.7
5th
out of 30 in Data Warehouse
Views
20,989
Comparisons
15,261
Reviews
4
Average Words per Review
267
Rating
8.3
Popular Comparisons
Compared 19% of the time.
Compared 16% of the time.
Compared 10% of the time.
Compared 16% of the time.
Compared 15% of the time.
Compared 13% of the time.
Compared 9% of the time.
Compared 4% of the time.
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Apache
Teradata
Overview
The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

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

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Sample Customers
Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web LabNetflix
Top Industries
VISITORS READING REVIEWS
Computer Software Company34%
Comms Service Provider17%
Financial Services Firm12%
Media Company6%
REVIEWERS
Comms Service Provider30%
Energy/Utilities Company20%
Manufacturing Company10%
Financial Services Firm10%
VISITORS READING REVIEWS
Computer Software Company39%
Comms Service Provider14%
Financial Services Firm8%
Media Company7%
Company Size
REVIEWERS
Small Business37%
Midsize Enterprise21%
Large Enterprise42%
REVIEWERS
Small Business27%
Midsize Enterprise9%
Large Enterprise64%
Find out what your peers are saying about Apache Hadoop vs. Teradata and other solutions. Updated: January 2021.
457,459 professionals have used our research since 2012.

Apache Hadoop is ranked 3rd in Data Warehouse with 10 reviews while Teradata is ranked 5th in Data Warehouse with 5 reviews. Apache Hadoop is rated 7.8, while Teradata is rated 8.2. The top reviewer of Apache Hadoop writes "Great micro-partitions, helpful technical support and quite stable". On the other hand, the top reviewer of Teradata writes "Good data warehousing, scalable, and offers good functionality". Apache Hadoop is most compared with VMware Tanzu Greenplum, Snowflake, Oracle Exadata, Vertica and Microsoft Azure Synapse Analytics, whereas Teradata is most compared with Oracle Exadata, SQL Server, Snowflake, Amazon Redshift and Teradata IntelliFlex. See our Apache Hadoop vs. Teradata report.

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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.