- Snowflake – Streams and Tasks
Native change tracking and scheduling, so a pipeline needs no extra orchestrator. What a stream really is (an offset, not a copy), the consumption rule that surprises everyone, task trees and serverless tasks, and the standard pattern: a stream feeds a MERGE, a task runs it only when there is something to do.
- Snowflake – Time Travel, Cloning and Undrop
The two features that change how you work, not just what you can recover. Querying a table as it was before the bad UPDATE, UNDROP, zero-copy clones that give you a full copy of production for a dev branch at no storage cost, and Fail-safe — which is Snowflake's insurance policy, not your backup.
- Snowflake – Making Queries Fast
Why a query is slow, in the order worth checking. Reading the Query Profile, pruning and what breaks it, spilling to local and remote storage and what to do about it, the three caches and which one you are actually hitting, and when clustering keys earn their cost — which is far less often than people reach for them.
- Snowflake – Querying Data
The SQL that is worth knowing beyond SELECT ... WHERE. CTEs, window functions, QUALIFY — the clause Snowflake has and Postgres does not — SAMPLE for exploring a large table cheaply, GROUP BY ALL, and the date and string functions that come up in every reporting query. All of it against TPCH_SF1.
- Snowflake – JSON and Semi-Structured Data
Loading JSON without designing a schema first, then querying it as if you had. The colon path syntax, casting out of VARIANT and why forgetting to cast makes strings come back with quotes, FLATTEN for arrays, and the decision that actually matters: when to leave data in a VARIANT column and when to shred it into real columns.