"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."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"The performance is pretty good."
"Hadoop is extensible — it's elastic."
"The flexibility in design is very good."
"I like this solution's ease of design and the fact that its performance is quite good. It is stable as well."
"It's a pre-configured appliance that requires very little in terms of setting-up."
"Teradata has good performance, the response times are very fast. Overall the solution is easy to use. When we do the transformation, we have all of our staging and aggregation data available."
"The functionality of the solution is excellent."
"Teradata features high productivity and reliability because it has several redundancy options, so the system is always up and running."
"The performance is great, we are able to query our data in one operation."
"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."
"Hadoop's security could be better."
"From the Apache perspective or the open-source community, they need to add more capabilities to make life easier from a configuration and deployment perspective."
"The solution is very expensive."
"I'm not sure about the unstructured data management capabilities. It could be improved."
"Teradata should focus on functionality for building predictive models because, in that regard, it can definitely improve."
"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."
"I would like to see more integration with many different types of data."
"It could use some more advanced analytics relating to structured and semi-structured data."
"The scalability could be better. The on-premises solution is always more complicated to scale."
"The solution is stable. However, there are times when we are using large amounts of data and we can see some latency issues."
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Apache Hadoop is ranked 7th in Data Warehouse with 5 reviews while Teradata is ranked 4th in Data Warehouse with 7 reviews. Apache Hadoop is rated 7.6, while Teradata is rated 8.4. 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 performance, flexible, easy to tune queries, and scales well". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Snowflake, VMware Tanzu Greenplum, Oracle Exadata and Vertica, whereas Teradata is most compared with Oracle Exadata, Snowflake, SQL Server, Amazon Redshift and IBM Db2 Database. See our Apache Hadoop vs. Teradata report.
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