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https://hudi.apache.org/blog/2026/08/04/migrating-from-delta-lake-to-hudi
Migrating from Delta Lake to Apache Hudi
Tags:
You can migrate a Delta Lake table to Apache Hudi either by translating its metadata with Apache XTable — no data rewrite required, since both formats store data as Apache Parquet — or by rewriting the table once with a Spark bulk_insert; many teams start by running
https://hudi.apache.org/vendors
Vendors are listed alphabetically; inclusion on this page is for the convenience of the community and does not imply endorsement by the Apache Software Foundation or the Apache Hudi project
https://hudi.apache.org/blog/2026/07/17/what-is-acid-on-a-data-lake
This post walks through what each of the four letters means concretely at the file level, how lakes worked before table formats existed, how formats like Apache Hudi deliver these guarantees, and — just as important — what ACID on a lake does not promise
https://hudi.apache.org/blog/2026/07/14/what-is-an-open-table-format
Apache Hudi, Apache Iceberg, Delta Lake, and Apache Paimon are the major open table formats; in all of them the data itself stays in open file formats like Apache Parquet or Apache ORC
https://hudi.apache.org/blog/2026/07/15/what-is-upsert-on-a-data-lake
How Open Table Formats Make Upserts Possible
Open table formats — Apache Hudi, Apache Iceberg, and Delta Lake — introduced a transactional metadata layer on top of immutable files, turning a directory of Parquet files into a proper table
https://hudi.apache.org/blog/2026/07/22/what-is-cdc-on-a-data-lake
Closing this gap is exactly why transactional table layers for the lake emerged; Apache Hudi, notably, grew out of the need to apply database change streams to lake storage at scale at Uber
https://hudi.apache.org/learn/tech-specs-0-point-x
Apache Hudi will manage metadata, and provide common abstractions and pluggable interfaces to most/all common compute/query engines
https://hudi.apache.org/blog/2026/07/17/async-compaction-background-maintenance
Tags:
This is the fourth post in a series on Merge-On-Read as an architectural shift in Apache Hudi
https://hudi.apache.org/blog/2026/07/16/what-is-incremental-etl-on-a-data-lake
Apache Hudi supports both query types on Copy-on-Write and Merge-on-Read tables
https://hudi.apache.org/powered-by
Adopters
Apache Hudi is a fast growing diverse community of people and organizations from all around the globe
https://hudi.apache.org/blog/2026/08/06/hudi-vs-iceberg-for-cdc-workloads
Apache Hudi vs Apache Iceberg for CDC Workloads
Tags:
Both Apache Hudi and Apache Iceberg can ingest change data capture (CDC) streams, but they were designed around different problems
https://fluss.apache.org
Data continuously tiers down to a Lakehouse cold tier (Apache Paimon, Apache Iceberg, Apache Hudi, Lance) via a Tiering Service
https://www.apache.org/foundation/leadership
, Apache BuildStream Abderrahim Kitouni
V
https://hudi.apache.org/docs/overview
This overview will provide a high level summary of what Apache Hudi is and will orient you on how to learn more to get started
https://www.apache.org/
Taking place on October 10, the event is dedicated to all things related to open lakehouse technologies under the Apache Software Foundation (ASF) umbrella, with content supporting Apache Iceberg™, Apache Hudi, Apache Parquet™, Apache Gravitino, Apache Polaris™, and more
https://kyuubi.apache.org
Data Lake & Lakehouses
Kyuubi supports query all traditional data warehouses, like Apache Hive/HDFS, or modern lakehouses, like Apache Iceberg, Apache Hudi, and Delta Lake, together
https://hudi.apache.org/blog/2026/07/21/what-is-a-streaming-data-lake
This post is the definitional companion to the original 2021 essay, Apache Hudi - The Data Lake Platform, which first articulated this vision in depth
https://hudi.apache.org/blog/2020/08/18/hudi-incremental-processing-on-data-lakes
Apache Hudi is a data lake framework which provides exactly this ability to ingest, manage and query large analytical data sets on a distributed file system/cloud stores
https://hudi.apache.org/blog/2026/07/23/lakehouse-vs-data-warehouse-vs-data-lake
Projects like Apache Hudi, Apache Iceberg, and Delta Lake define tables (not just files) over Parquet and ORC, and bring the database capabilities the lake was missing:
ACID transactions with concurrency control, so writers commit atomically and readers never see partial results
https://inlong.apache.org/docs/2.3.0/introduction
inlong-sort, after consuming data from different MQ services, perform ETL processing, and then aggregate and write the data into Apache Hive, ClickHouse, HBase, IceBerg, Hudi, etc
https://hudi.apache.org/docs/indexes
g: Apache Hive/Apache Iceberg) end up having to merge all the base files against all incoming updates/delete records (10-100x more read amplification)
https://directory.apache.org/apacheds
Apache Directory
LDAP and Kerberos server written in Java
ApacheDS™ is an extensible and embeddable directory server entirely written in Java, which has been certified LDAPv3 compatible by the Open Group
https://hudi.apache.org/learn/tech-specs
Syntax
note
This document specifies the current storage format — table version 9, as shipped through Hudi 1
https://ant.apache.org
the Apache Ant site
Apache Ant™
Apache Ant is a Java library and command-line tool whose mission is to drive processes described in build files as targets and extension points dependent upon each other
https://directory.apache.org/commercial-support.html
The Apache Directory™ PMC does not endorse or recommend any of the products or services on this page
https://velocity.apache.org/
When Velocity is used for web development, Web designers can work in parallel with Java programmers to develop web sites according to the Model-View-Controller (MVC) model, meaning that web page designers can focus solely on creating a site that looks good, and programmers can focus solely on writing top-notch code
https://attic.apache.org/
This site uses Just the Docs, a documentation theme for Jekyll
https://www.apache.org/security
org websites)
The general security mailing list address is: security@apache
https://forrest.apache.org/
Much effort has gone into making the process of generating a new site easy and simple:
Step 1: Do 'forrest seed' to populate the directory with template site structure and contents
https://www.apache.org/foundation/marks/events
For more information on use of Apache marks in other areas, see our formal Trademark Policy and site map of resources