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



Big Data from Sensor Networks

What have drones or Boeings in common with NoSQL? The answer even if not obvious is Big Data.

We’re always amazed about the amount of digital content created by humans online. But if we look at sensor networks things are even more impressive:

For example, a Boeing jet generates 10 terabytes of information per engine every 30 minutes of flight, according to Stephen Brobst, the CTO of Teradata. So for a single six-hour, cross-country flight from New York to Los Angeles on a twin-engine Boeing 737 — the plane used by many carriers on this route — the total amount of data generated would be a massive 240 terabytes of data. There are about 28,537 commercial flights in the sky in the United States on any given day. Using only commercial flights, a day’s worth of sensor data quickly climbs into the petabyte scale — for a single day. Multiply that by weeks, months and years, and the scale of sensor data gets massive.


And the problem is two fold: storage and processing. Truth being told, things are even more complicated than this.

Original title and link: Big Data from Sensor Networks (NoSQL databases © myNoSQL)