- amazon dyno (dynamo?) - cassandra -- latest time stamp wins
- managing distributed records -- use checksum to verify data health
- why use an hbase -- random reads on disks are slow; reading from sequential data on disk is the only way to go -- simple fetch queries are roughly equivalent to an hbase lookup
- hdfs / hbase division?
- how to update record? -- hbase is not replacing relational dbs; they are used in conjunction. -- they can replace relational dbs, if the data we’re storing is normalized by nature, eg we’re just using it for user records -- if the data is actually normalized in the hbase, the update is straightforward. If the data is denormalized in the hbase, we’re better off having the data normalized in a relational db, updating the normal db, and then updating the hbase in a batch process later.
- memcache vs hbase
- db sharding -- painful because it’s application logic and relational dbs are optimized for joins. -- hbase is optimized for sharding