---
title: "What is incremental computation?"
description: "Incremental computation recomputes only the rows and downstream columns a change actually affects, instead of rerunning the whole pipeline."
url: "https://pixeltable.com/learn/what-is-incremental-computation"
updated: "2026-09-29"
vertical: "Orchestration"
doc: "https://docs.pixeltable.com/datastore/computed-columns"
---

# What is incremental computation?

Incremental computation recomputes only the rows and downstream columns a change actually affects, instead of rerunning the whole pipeline.

Updated: 2026-09-29


## On this page

- [How it works](https://pixeltable.com/learn/what-is-incremental-computation#how-it-works)
- [What it is not](https://pixeltable.com/learn/what-is-incremental-computation#what-it-is-not)
- [Comparison](https://pixeltable.com/learn/what-is-incremental-computation#comparison)
- [Where Pixeltable fits](https://pixeltable.com/learn/what-is-incremental-computation#where-pixeltable-fits)
- [Questions](https://pixeltable.com/learn/what-is-incremental-computation#questions)

## How it works {#how-it-works}


- Dependencies between columns are known.
- An edit marks the descendants of that row.
- Everything else stays cached.

## What it is not {#what-it-is-not}

It is not a nightly full refresh, and it is not a cache you remember to invalidate.

## incremental computation: this, and the thing it is confused with {#comparison}

|  | This | Not this |
| --- | --- | --- |
| Work | Changed rows | The whole table |
| Invalidation | Recorded dependencies | Hope |
| Cost | Model calls for the delta | Model calls for the corpus |

## Where Pixeltable fits {#where-pixeltable-fits}

Pixeltable tracks those dependencies on computed columns. A new file recomputes that row’s descendants.

## Questions {#questions}

### How does incremental computation work? {#faq-1}

Dependencies between columns are known. An edit marks the descendants of that row. Everything else stays cached.

### What is incremental computation often confused with? {#faq-2}

It is not a nightly full refresh, and it is not a cache you remember to invalidate.

## In the blog

- [Beyond Pandas: Why Pixeltable Is the Ultimate Tool for Multimodal Data Wrangling](https://pixeltable.com/blog/pixeltable-vs-pandas-multimodal-data-wrangling)
- [Compute Close to Data: What Microsoft's pg_durable Says About Where AI Infrastructure Is Going](https://pixeltable.com/blog/pg-durable-compute-close-to-data-multimodal-pixeltable)
- [Iterate on Your Data, Not Your Infrastructure: The Multimodal Experimentation Loop](https://pixeltable.com/blog/iterate-on-data-not-infrastructure)
- [Neon Functions vs Pixeltable Computed Columns](https://pixeltable.com/blog/neon-functions-vs-pixeltable-computed-columns)
- [What Is a Multimodal Data Table?](https://pixeltable.com/blog/what-is-a-multimodal-data-table)
- [Databricks FILE Type vs Pixeltable Media Columns](https://pixeltable.com/blog/databricks-file-type-vs-pixeltable-media-columns)

## Related

- [Documentation](https://docs.pixeltable.com/datastore/computed-columns)
- [The Economics of Incremental AI: Stopping the Re-computation Cash Burn](https://pixeltable.com/blog/economics-of-incremental-ai)
- [Declarative, Multimodal, Incremental AI Infrastructure with Pixeltable](https://pixeltable.com/blog/declarative-multimodal-incremental)
- [Dependency Graph Magic: How Pixeltable Keeps Your AI Pipeline Data Consistent](https://pixeltable.com/blog/dependency-graph-magic-computed-columns)
- [Incremental updates](https://pixeltable.com/use-cases/incremental-updates-ai-data-processing)