Understanding Snowflake Table Locks

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Introduction

Table locks are not just for DBAs; data engineers must also understand how to manage concurrent transactions from multiple applications to the same database table. Properly managing table locks is crucial for ensuring data consistency, preventing conflicts, and maintaining the integrity of your data. As data pipelines become more complex and the volume of transactions increases, understanding how table locks work can help data engineers design more robust and reliable data workflows.

Table locks in Snowflake

Before jumping into locks, let’s first state a few important definitions…

• Session — A state of information exchange between a client and Snowflake. A session begins after a user has successfully connected and authenticated with Snowflake.
• Transaction — A sequence of SQL statements processed as one atomic unit. In other words, either all or none of the statements succeed.
• Isolation Level — The degree to which a transaction must be isolated from the data modifications made by another transaction.
• Read Committed— Snowflake’s only isolation level. Within a transaction, a statement only sees data that has been committed.