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Change Data Capture with Debezium and Apache Hudi
Tags:
As of Hudi v0
from the top result below
https://hudi.apache.org/blog/2022/01/14/change-data-capture-with-debezium-and-apache-hudi
Change Data Capture with Debezium and Apache Hudi
Tags:
As of Hudi v0
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/powered-by
Apache Hudi is used to perform ingest MySQL and PostgreSQL change data capture
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/2026/07/15/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/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/blog/2026/07/28/using-hudi-with-apache-iceberg-via-xtable
Using Apache Hudi with Apache Iceberg: Interoperability via Apache XTable
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Yes — Apache Iceberg engines and catalogs can read Apache Hudi tables
https://hudi.apache.org/docs/quick-start-guide
13
spark-shell --master "local[2]" \
--packages org
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/2026/07/23/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://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/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/learn/tech-specs
Syntax
note
This document specifies the current storage format — table version 9, as shipped through Hudi 1