Greybeam's multi-query-engine dream is slowly becoming a reality. Lately, we've been encountering more and more data teams who are looking to offload non-critical workloads to alternative compute engines like
Welcome to part two in our series of working with Iceberg tables. If you haven't already setup your Snowflake managed Iceberg tables, be sure to check out part one in our
As data teams increasingly adopt Apache Iceberg for their data lake needs, we will begin to see a need for better tooling in the space. At the moment pyIceberg is the go to
At Greybeam, we're constantly exploring ways to optimize Snowflake, and I'm so thrilled that our journey led us to Iceberg and DuckDB. In this post, we'll cover
ASOF JOINs are the most efficient way to relate the timestamp of one table with the timestamp of another table, even when those timestamps don't match exactly.
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