Not in production yet, but my company's in the process of moving from Infobright to Redshift, mostly because Infobright, while extremely fast, is a single-server solution and we think that within a year we'll have outgrown its capacity.
Our data is 3 denormalized tables with the same ~1000 column schema, the largest of which contains 7B rows. Most of our queries are simple aggregations down a few columns, with simple constraints like date range + customer ID.
So far we're really impressed with Redshift's load performance and ease of getting up-and-running, but we're still an order of magnitude away from Infobright's query performance. Next steps are playing with distribution and sort keys, as well as trying different cluster configurations; to be fair to Redshift we've not run it on more than a 6 XL cluster yet.
Our data is 3 denormalized tables with the same ~1000 column schema, the largest of which contains 7B rows. Most of our queries are simple aggregations down a few columns, with simple constraints like date range + customer ID.
So far we're really impressed with Redshift's load performance and ease of getting up-and-running, but we're still an order of magnitude away from Infobright's query performance. Next steps are playing with distribution and sort keys, as well as trying different cluster configurations; to be fair to Redshift we've not run it on more than a 6 XL cluster yet.