vinothchandar commented on code in PR #19268: URL: https://github.com/apache/hudi/pull/19268#discussion_r3567903611
########## website/src/pages/faq/general.md: ########## @@ -7,10 +7,28 @@ keywords: [hudi, writing, reading] ### When is Hudi useful for me or my organization? -If you are looking to quickly ingest data onto HDFS or cloud storage, Hudi provides you [tools](/docs/hoodie_streaming_ingestion). Also, if you have ETL/hive/spark jobs which are slow/taking up a lot of resources, Hudi can potentially help by providing an incremental approach to reading and writing data. +If you are looking to quickly ingest data onto HDFS or cloud storage, Hudi provides you [tools](/docs/hoodie_streaming_ingestion). Also, if you have ETL/hive/spark jobs which are slow/taking up a lot of resources, Hudi can potentially help by providing an incremental approach to reading and writing data. Hudi remains the de facto lakehouse format for fast incremental writes and reads, and it ships with automated table maintenance built in, so tables stay optimized without external orchestration. As an organization, Hudi can help you build an [efficient data lake](https://docs.google.com/presentation/d/1FHhsvh70ZP6xXlHdVsAI0g__B_6Mpto5KQFlZ0b8-mM/edit#slide=id.p), solving some of the most complex, low-level storage management problems, while putting data into hands of your data analysts, engineers and scientists much quicker. +### What makes Hudi different from other lakehouse formats? + +Hudi offers a set of core capabilities today that other lakehouse formats do not. The [21 unique differentiators](/blog/2025/03/05/hudi-21-unique-differentiators) post covers the technical crux in depth; the highlights are: + +* **_Multi-modal indexing:_** Hudi maintains a range of [indexes](/docs/indexes) — record-level indexes, bloom filters, bucket indexes and more — that speed up upserts and deletes on the write side, plus read-side secondary indexes (including expression indexes on columns) that prune queries, much like a relational database. +* **_Non-blocking concurrency control:_** Hudi's MVCC-based [concurrency control](/docs/concurrency_control#non-blocking-concurrency-control) lets multiple writers and table services modify a table concurrently without failing or blocking each other, avoiding wasted compute from retries and livelocks. +* **_Async compaction and built-in table services:_** compaction, clustering, cleaning, file sizing, indexing and archival are scheduled and executed automatically alongside writes — no external orchestration or manual maintenance commands. Hudi is the only lakehouse project that can rapidly ingest data while handling small-file compaction without blocking those writes. This kind of table maintenance is something you typically pay a vendor for; in Hudi it is open source and built in. Review Comment: it remains defensible. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
