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title: Delta Lake - State of the Project - Part 2 | daily.dev
description: This second installment of Delta Lake's state-of-the-project review covers interoperability and performance improvements over the past year. Delta UniForm now...
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og:description: This second installment of Delta Lake's state-of-the-project review covers interoperability and performance improvements over the past year. Delta UniForm now...
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# Delta Lake - State of the Project - Part 2

**[Delta Lake Blog](https://daily.dev/sources/delta-lake)** · 9 min read · 0 upvotes · 0 comments

## Summary

This second installment of Delta Lake's state-of-the-project review covers interoperability and performance improvements over the past year. Delta UniForm now lets Delta tables expose Iceberg metadata without duplicating data, with Hudi support in progress. Delta Kernel simplifies building connectors via Java and Rust libraries, already adopted by Apache Druid and reducing Flink pipeline initialization time by 45x. Connector updates span Flink, Trino, Druid, delta-rs (2M+ monthly PyPI downloads), Delta Sharing, a new .NET binding, and a from-scratch Go connector by Rivian. On performance, Deletion Vectors deliver 2x DELETE speedups since Delta 2.4, 10x UPDATE since Delta 3.0, and 3.7x MERGE since Delta 3.1, alongside Optimized Write and Auto Compaction addressing the small file problem. The post closes by teasing Delta 4.0 alongside the upcoming Spark 4.0 release.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://delta.io/blog/state-of-the-project-pt2>

## Questions this post answers

### What is Delta Lake UniForm and how does it enable Iceberg compatibility?

Delta Lake Universal Format (UniForm) automatically writes Iceberg metadata alongside Delta metadata on the same Parquet data files, so Delta-compliant and Iceberg-compliant engines can read the same table without conversion or duplicate copies. Support for Hudi metadata is also being added by the community. A one-time, zero-copy, in-place conversion from Iceberg to Delta tables is also available.

_Teams weighing table format lock-in can follow lakehouse interoperability developments on daily.dev._

### How much did Delta Kernel improve Flink pipeline initialization time?

The experimental Kernel integration in the Flink Sink connector reduced Flink pipeline initialization time by 45x, driven by faster table metadata fetches, when writing to an 11 petabyte table containing 7 million files, as introduced in Delta Lake 3.1. Delta Kernel is a library available in Java and Rust that abstracts protocol details behind stable APIs for connector developers.

_Engineers tuning streaming pipeline startup latency can track connector performance work on daily.dev._

### What performance improvements did Deletion Vectors bring to Delta Lake MERGE, UPDATE, and DELETE operations?

Deletion Vectors delivered a 2x speedup for DELETE since Delta 2.4, a 10x speedup for UPDATE since Delta 3.0, and a 3.7x speedup for MERGE since Delta 3.1, all without hurting read performance despite typical merge-on-read tradeoffs. Even without enabling deletion vectors, merges are 2x faster since Delta 3.0.

_Data engineers optimizing table write performance can keep up with Delta Lake benchmarks on daily.dev._

## Similar posts on daily.dev

- [Advancing the Open Lakehouse with Apache Spark, the Delta Kernel, and the new UC Delta APIs](https://daily.dev/posts/advancing-the-open-lakehouse-with-apache-spark-the-delta-kernel-and-the-new-uc-delta-apis-dbaazlwws) · Delta Lake Blog · 0 upvotes · 0 comments
- [Delta Kernel \(Rust\) and the future of the Lakehouse.](https://daily.dev/posts/delta-kernel-rust-and-the-future-of-the-lakehouse--twurulaae) · Confessions of a Data Guy · 16 upvotes · 1 comments
- [Advancing the Lakehouse with Apache Iceberg v3 on Databricks](https://daily.dev/posts/advancing-the-lakehouse-with-apache-iceberg-v3-on-databricks-6p6wf37qi) · databricks · 4 upvotes · 0 comments
- [Apache Iceberg vs Delta Lake: Choosing the Right Table Format](https://daily.dev/posts/apache-iceberg-vs-delta-lake-choosing-the-right-table-format-vtnia2ems) · BigData Boutique blog · 7 upvotes · 0 comments

---

Tags: [#rust](https://daily.dev/tags/rust), [#data-engineering](https://daily.dev/tags/data-engineering), [#apache-spark](https://daily.dev/tags/apache-spark), [#apache-iceberg](https://daily.dev/tags/apache-iceberg)

[View this post on daily.dev](https://daily.dev/posts/delta-lake---state-of-the-project---part-2-tynxxnvdr)

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