mtraverso

We started the project with 4 full-time engineers and added a fifth person recently. We began working on Presto in August last year and deployed our first working version in January, and we've been iterating on it ever since.

One big advantage we have that speeds up development is the Facebook culture of moving fast and shipping often. Facebook employees are used to working with software as it's being built and refined. This kept us focused on the key subset of features that matter to users and getting close to realtime feedback from them. Our development cycle is typically one release and push to production per week.

Also, from the beginning Presto had to work with current Facebook infrastructure (100s of machines, 100s of petabytes), so we faced and solved all the associated scaling challenges up-front.

Airlift is a toolkit for building distributed services and it is the foundation of Presto. For the most part, it's a convenience layer on top of some well-known libraries (Jackson, Jersey, Jetty, Guice, etc.), but it also has support for various things you'd typically need to build a deployable server, such as packaging, configuration, logging, instrumentation (stats), etc.

Unfortunately, we don't have any docs, so you'll just have to peruse the code. There's minimal server in the codebase to demonstrate usage of some of its features: https://github.com/airlift/airlift/tree/master/sample-server

We don't have a connector for flat binary records or plain HDFS, but you can take a look at the Hive connector here: https://github.com/facebook/presto/tree/master/presto-hive/s...

We're also working on a example connector that can read from files/urls. We should have that code up soon.

I can't speak to what other products like Impala, Apache Drill, etc. offer, but Presto supports the following:

- Standard ANSI SQL syntax, including all the basic features you'd expect from a SQL engine (aggregations, joins, etc) and other more advanced features like analytic window functions, common table expressions (WITH), approximate distinct counts and percentiles.

- It's extensible. The open source code base includes a connector for Hive, but we also have some custom connectors for internal data stores at Facebook. We're working on a connector for HBase, too.

- In comparison to Hive, it's very fast and efficient. For our workloads it's at least 10x more CPU-efficient. Airbnb is using it and has had a similar experience.

- Most importantly, Presto has been battle-tested. It's been in production at Facebook since January and it's used by 1,000 employees every day running 30,000 queries daily. We've hit every edge case you can imagine.