Firebolt — the new kid on the (data warehousing) block

A short description of Firebolt, for not-so-technical people

Recently, we started using Looker for ad-hoc queries of business users in the company (PMs, managers, marketing, and basically everyone). One main problem we have though, is that our Looker performance is pretty bad — queries just take too long.

Harry Potter receives his own Firebolt from Sirius Black

What is Firebolt?

Firebolt is a data warehouse that lets you ingest your data to their dedicated storage with a proprietary format called F3 (pronounced “TripleF”). Like Snowflake, it provides you with separated compute units called Firebolt Engines to query that data (and to ingest it).

How it works?

The speed is achieved mainly through efficient data scanning (Firebolt claims to scan significantly less data == less I/O == faster queries) using Sparse Indices. It basically means that per-table, you define the fields that are going to appear in your WHERE clause, and Firebolt sorts, partitions, and indexes the table by those fields.

  • Join Index: if you know some tables are being joined often, you can create this index that generates look-up tables and other optimizations on the relevant fields of the tables, in order to perform the joins faster.

Connectivity

Currently there are 2 ways to integrate with Firebolt:

  1. Their REST API

Summary

Firebolt seems like a very elegant solution to the performance problem we all have with ad-hoc and interactive queries. If they actually deliver what they claim to — I guess Snowflake now has a scary competitor.

The new needs friends

— Anton Ego, Ratatouille

If you face the challenge of slow performance in your BI tools, I think you should check them out. And after you did — it would be pretty helpful if you’d share in the comments your findings from using Firebolt.

I like data-backed answers

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