NoSQL Benchmarks NoSQL use cases NoSQL Videos NoSQL Hybrid Solutions NoSQL Presentations Big Data Hadoop MapReduce Pig Hive Flume Oozie Sqoop HDFS ZooKeeper Cascading Cascalog BigTable Cassandra HBase Hypertable Couchbase CouchDB MongoDB OrientDB RavenDB Jackrabbit Terrastore Amazon DynamoDB Redis Riak Project Voldemort Tokyo Cabinet Kyoto Cabinet memcached Amazon SimpleDB Datomic MemcacheDB M/DB GT.M Amazon Dynamo Dynomite Mnesia Yahoo! PNUTS/Sherpa Neo4j InfoGrid Sones GraphDB InfiniteGraph AllegroGraph MarkLogic Clustrix CouchDB Case Studies MongoDB Case Studies NoSQL at Adobe NoSQL at Facebook NoSQL at Twitter



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)