Dremel: All content tagged as Dremel in NoSQL databases and polyglot persistence
Monday, 29 October 2012
Overview of Dremel-Like Solutions: Moving Beyond Hadoop for Big Data Needs
Until I learn more about the recently announced Cloudera Impala and Druid from Metamarkets, this article by Jaikumar Vijayan should offer—with some inherent mistakes1—a good overview of the solutions aiming to offer alternatives to the batch-processing nature of Hadoop:
- Google Dremel (BigQuery)
- Cloudera Impala
- Metamarkets Druid
- Nodeable StreamReduce
- SAP HANA integrated with Hadoop, etc.
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Just an example: “If you can stand latencies of a few seconds, Hadoop is fine. But Hadoop MapReduce is never going to be useful for sub-second latencies”. Then “The technology [nb Google Dremel] can run queries over trillion-row data tables in seconds…”
Maybe just one more: consider the title “Moving beyond Hadoop” and then the quote from Google’s Ju-kay Kwek: “Google uses Dremel in conjuction with MapReduce. […] Hadoop and Dremel are distributed computing technologies, but each was built to address very different problems.” ↩
Original title and link: Overview of Dremel-Like Solutions: Moving Beyond Hadoop for Big Data Needs (©myNoSQL)
Monday, 11 October 2010
Google's Dremel: Can MapReduce Handle Fast, Interactive Querying?
A bit old, but thought that in the light of latest posts about MapReduce and Hadoop future, it made sense to have this piece of the puzzle too.
Tasso Argyros (AsterData):
Native MapReduce execution is not fundamentally slow; however Google’s MapReduce and Hadoop happen to be oriented more towards batch processing. Dremel tries to overcome that by building a completely different system that speeds interactive querying.
The Dremel: Interactive Analysis of Web-Scale Datasets paper can be downloaded from ☞ here (PDF).
Original title and link: Google’s Dremel: Can MapReduce Handle Fast, Interactive Querying? (NoSQL databases © myNoSQL)
