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title: Designing Right-Time Data Ingestion Pipelines in Snowflake
description: Right-time data ingestion means matching pipeline latency to actual business needs rather than defaulting to either batch or streaming. Using Snowflake...
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# Designing Right-Time Data Ingestion Pipelines in Snowflake

**[Snowflake Community](https://daily.dev/sources/snowflake_comm)** · 7 min read · 0 upvotes · 0 comments

## Summary

Right-time data ingestion means matching pipeline latency to actual business needs rather than defaulting to either batch or streaming. Using Snowflake alongside Estuary, data engineers can configure per-table ingestion patterns — from scheduled batch loads to CDC-based micro-batches to full streaming — within a single platform. Key techniques include using MERGE statements with min/max field bounds to reduce table scans, incremental CDC ingestion to avoid redundant full refreshes, and configurable polling and sync intervals. The post outlines best practices: understand acceptable lag per use case, prefer incremental over full refreshes, and favor a unified tool over stitching multiple ingestion systems together.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/snowflake/designing-right-time-data-ingestion-pipelines-in-snowflake-03bee3c818df>

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---

Tags: [#backend](https://daily.dev/tags/backend), [#data-engineering](https://daily.dev/tags/data-engineering), [#snowflake](https://daily.dev/tags/snowflake), [#change-data-capture](https://daily.dev/tags/change-data-capture)

[View this post on daily.dev](https://daily.dev/posts/designing-right-time-data-ingestion-pipelines-in-snowflake-ivokahy9x)

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