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title: Delta 2.0 - The Foundation of your Data Lakehouse is Open
description: Delta Lake 2.0 has been released for Apache Spark 3.2, adding change data feed support, Z-Order clustering for better data skipping, idempotent table writes,...
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og:description: Delta Lake 2.0 has been released for Apache Spark 3.2, adding change data feed support, Z-Order clustering for better data skipping, idempotent table writes,...
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# Delta 2.0 - The Foundation of your Data Lakehouse is Open

**[Delta Lake Blog](https://daily.dev/sources/delta-lake)** · 10 min read · 0 upvotes · 0 comments

## Summary

Delta Lake 2.0 has been released for Apache Spark 3.2, adding change data feed support, Z-Order clustering for better data skipping, idempotent table writes, column dropping as a metadata-only operation, dynamic partition overwrite, and experimental multi-part checkpointing. The release marks the project's third birthday and reinforces Databricks' commitment to keeping Delta Lake fully open source, alongside new connectors for Apache Flink, Presto, and Trino. Monthly downloads grew from 685K to over 7M in a year, with contributor strength up 633% over three years.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://delta.io/blog/2022-08-02-delta-2-0-the-foundation-of-your-data-lake-is-open>

## Questions this post answers

### What new features does Delta Lake 2.0 add for Apache Spark 3.2?

Delta Lake 2.0, released for Apache Spark 3.2, adds support for change data feed, Z-order clustering for improved data skipping, idempotent writes to Delta tables, dropping columns as a metadata-only operation, dynamic partition overwrite, and experimental multi-part checkpointing. Monthly downloads grew from 685K to over 7M in the prior year.

_Teams planning a Delta Lake upgrade can track new release capabilities like this on daily.dev._

### How do I enable change data feed on a Delta Lake table?

Set the table property delta.enableChangeDataFeed = true in a CREATE TABLE command for new tables, or in an ALTER TABLE command for existing tables. Once enabled, only changes made after activation are captured, and tables can no longer be written to using Delta Lake 1.2.1 or below, though reads remain unaffected.

_Engineers wiring up streaming pipelines follow changes like this via daily.dev._

### Why is dropping a column in Delta Lake 2.0 fast compared to older versions?

Dropping a column in Delta Lake 2.0 is a metadata-only operation because it leverages column mapping between logical and physical Parquet column names, introduced in Delta Lake 1.2. Instead of rewriting every underlying data file, the transaction log is simply updated to reflect the column removal, making it far cheaper than the pre-1.2 requirement of matching Parquet file names to table schema.

_Data engineers weighing schema-evolution trade-offs keep up with changes like this on daily.dev._

## Similar posts on daily.dev

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---

Tags: [#open-source](https://daily.dev/tags/open-source), [#backend](https://daily.dev/tags/backend), [#data-engineering](https://daily.dev/tags/data-engineering), [#apache-spark](https://daily.dev/tags/apache-spark)

[View this post on daily.dev](https://daily.dev/posts/delta-2-0---the-foundation-of-your-data-lakehouse-is-open-7fqvz5y80)

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