We performed a comparison between Apache Hadoop and Infobright DB based on real PeerSpot user reviews.
Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse."As compared to Hive on MapReduce, Impala on MPP returns results of SQL queries in a fairly short amount of time, and is relatively fast when reading data into other platforms like R."
"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."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"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."
"We selected Apache Hadoop because it is not dependent on third-party vendors."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."
"Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"It has very amazing smart grid query feature for very fast aggregate queries across millions of rows"
"It could be more user-friendly."
"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."
"The solution is very expensive."
"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."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"The stability of the solution needs improvement."
"The upgrade path should be improved because it is not as easy as it should be."
"The price could be better. I think we would use it more, but the company didn't want to pay for it. Hortonworks doesn't exist anymore, and Cloudera killed the free version of Hadoop."
"Only the data from the columns that reached 2GB will actually decrease. Other columns below 2GB in size do not leave the disk."
Earn 20 points
Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews while Infobright DB is ranked 27th in Data Warehouse. Apache Hadoop is rated 7.8, while Infobright DB is rated 7.6. The top reviewer of Apache Hadoop writes "A file system for data collection that contains needed information and files". On the other hand, the top reviewer of Infobright DB writes "If you need a real big data solution, look for a distributed solution that actually has a proven track record". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata, whereas Infobright DB is most compared with MySQL and LocalDB.
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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.
