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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
from the top result below
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/2026/08/04/migrating-from-delta-lake-to-hudi
Option A: Convert with Apache XTable
Apache XTable (incubating) is an open source project that translates table metadata between Delta Lake, Hudi, and Iceberg in any direction, without copying or rewriting data files
https://hudi.apache.org/blog/2021/07/21/streaming-data-lake-platform
Apache Hudi - The Data Lake Platform
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Apache Hudi is a streaming data lake platform built around a database kernel—not merely a table format or a transactional layer, but a complete software stack with built-in table services, data services, and incremental processing capabilities
https://hudi.apache.org/blog/2022/01/14/change-data-capture-with-debezium-and-apache-hudi
Now that Apache Hudi offers a Debezium source connector, CDC ingestion into a data lake is easier than ever with some unique differentiated capabilities
https://hudi.apache.org/contribute/developer-setup
Once cloned, build Hudi by following Building Apache Hudi from source in the README, which also covers building against a specific Spark version or Flink version
https://hudi.apache.org/blog/2026/08/05/migrating-from-apache-iceberg-to-hudi
Migrating from Apache Iceberg to Apache Hudi
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You can adopt Apache Hudi on an existing Apache Iceberg table either by translating its metadata with Apache XTable — no data rewrite, since both formats store data as Parquet files — or via a one-time rewrite; and because XTable also works in the reverse direction
https://hudi.apache.org/docs/concurrency_control
Hudi ensures atomic writes by publishing commits atomically to the timeline, stamped with an instant time that denotes when the action is deemed to have occurred
https://hudi.apache.org/blog/2026/08/12/hudi-vs-delta-lake-for-write-heavy-workloads
Apache Hudi vs Delta Lake for Write-Heavy Workloads
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For update- and delete-heavy tables, the core architectural difference is this: Apache Hudi locates the records being changed through pluggable indexes — including a record-level index that maps each key to its file group — and can absorb changes into Merge
https://hudi.apache.org/contribute/security
If you have apprehensions regarding Hudi's security, or you discover vulnerability or potential threat, don’t hesitate to get in touch with the Apache Security Team by dropping a mail at security@apache
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/powered-by
The following is a small sample of companies that have adopted or contributed to the Apache Hudi community
https://hudi.apache.org/blog/2026/08/06/hudi-vs-iceberg-for-cdc-workloads
Apache Hudi vs Apache Iceberg for CDC Workloads
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Both Apache Hudi and Apache Iceberg can ingest change data capture (CDC) streams, but they were designed around different problems
https://hudi.apache.org/blog/2026/07/30/migrating-from-hive-to-hudi
Migrating from Apache Hive Tables to Apache Hudi
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Migrating an Apache Hive table to Apache Hudi means converting its underlying data files into a Hudi table — either in place with Hudi's bootstrap mechanism or by rewriting the data with Spark — and re-registering it in your metastore through Hudi's catalog
https://hudi.apache.org/docs/overview
Try out these Quick Start resources to get up and running in minutes:
Unstructured Data Quick Start Guide – store embeddings (VECTOR) and raw bytes (BLOB) and run similarity search with hudi_vector_search
If you want to experience Apache Hudi integrated into an end to end demo with Kafka, Spark, Hive, Presto, etc
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/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/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://hudi.apache.org/blog/2026/08/11/hudi-vs-iceberg-for-streaming-ingestion
Apache Hudi vs Apache Iceberg for Streaming Ingestion
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Both Apache Hudi and Apache Iceberg can ingest streaming data, but they are built around different assumptions about how often a table is written to
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
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This is the fourth post in a series on Merge-On-Read as an architectural shift in Apache Hudi
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://hudi.apache.org/vendors
Vendors
The following vendors provide managed services, cloud platform integrations, or commercial support for Apache Hudi