Onehouse Blog
onehouse.ai · Company blog · on HN since 2023
Onehouse, a data lakehouse company built by the team behind Apache Hudi, writes about table formats, catalogs, and analytics engine benchmarks.
What HN saysCommenters call its Hudi vs Delta Lake vs Iceberg comparison the best reference for the three formats, though one suspects the source has a competitor's bias.
21HN people shared it
9linked it in comments
16stories submitted
64story points
5 months agolast shared
2023people per year2026
Most-shared posts
- 12025 Analytics Engine Ranking4 people · 11 points · first shared 2025 · 2 comments on HN
- 2Apache Hudi vs. Delta Lake vs. Apache Iceberg Lakehouse Feature Comparison4 people · 6 points · first shared 2023 · discussion on HN
- 3Onetable Interop Layer for Apache Hudi, Delta Lake and Apache Iceberg2 people · 13 points · first shared 2023 · 1 comments on HN
- 4Comprehensive Data Catalog Comparison2 people · 8 points · first shared 2024 · 3 comments on HN
- 5Open Table Formats and the Open Data Lakehouse, in Perspective2 people · 3 points · first shared 2025 · discussion on HN
- 6Has the lakehouse battle shifted from table formats to catalogs?2 people · 2 points · first shared 2026 · discussion on HN
- 7Apache hudi vs delta lake transparent tpc ds lakehouse performance benchmarks2 people · first shared 2023
- 8Cloud Warehouse/Lakehouse ETL Benchmarking Across EMR, Snowflake, Databricks1 people · 8 points · first shared 2025 · 2 comments on HN
- 9Interoperable Lakehouse: Difference Between Onetable and UniForm1 people · 6 points · first shared 2023 · discussion on HN
- 10A new DB for Iceberg/Hudi because low-latency serving on a lake is impractical1 people · 4 points · first shared 2026 · discussion on HN
- 11Inflated data lakehouse costs and latencies? – Blame S3's choice of HTTP/1.11 people · 2 points · first shared 2026 · discussion on HN
- 12Acid Transactions in an Open Data Lakehouses (Iceberg, Hudi, Delta Lake)1 people · 1 points · first shared 2025 · discussion on HN
- 13Why data architecture should guide your query engine decision1 people · first shared 2025
- 14Open data foundations with apache xtable hudi delta and iceberg interoperability1 people · first shared 2025
What HN people wrote when they linked it
jamesblonde · 2025-10-13
Here's a good performance study by OneHouse comparing Clickhouse, StarRocks, Trino:
https://www.onehouse.ai/blog/apache-spark-vs-clickhouse-vs-presto-vs-s…
Druid is real-time analytics, similar to Clickhouse. StarRocks is best at Joins - Clickhouse is not good for joins.
rdegges · 2025-01-26
OneHouse also has a fantastic iceberg implementation (they're the team behind Apache Hudi) and does a ton of great interop work: https://www.onehouse.ai/blog/comprehensive-data-catalog-comparison && https://www.onehouse.ai/blog/open-data-foundations-with-apache-xtable-…
alpdhuez77 · 2024-01-18
This is the best reference for comparing the 3 formats:
https://www.onehouse.ai/blog/apache-hudi-vs-delta-lake-vs-apache-icebe…
xnx · 2024-01-19
More comparisons (from a competitor?):
"Apache Hudi vs Delta Lake vs Apache Iceberg - Data Lakehouse Feature Comparison" https://www.onehouse.ai/blog/apache-hudi-vs-delta-lake-vs-apache-icebe…
benjaminwootton · 2024-01-18
Thanks for the upvotes.
Here is a more technical deep dive comparing the three main open formats - https://www.onehouse.ai/blog/apache-hudi-vs-delta-lake-vs-apache-icebe…
sivabalan · 2023-06-30
Interesting to see they took inspiration from Onehouse on the unified table format Ref dated Feb, 2023: https://www.onehouse.ai/blog/onetable-hudi-delta-iceberg
And another big player (SF) is also starting to support additional table formats.
sla99 · 2023-01-14
It looks like the benchmarks used the latest versions of Delta and Iceberg, but chose a version of Hudi that is over 6 months old. Hudi v0.12.2 is much more advanced than v0.12.0 which the benchmark did not consider. As the Databricks CIDR paper states, and as mentioned in the Onehouse article, Hudi by default is optimized for UPSERTs vs INSERTs and is a 1-line config change that is appropriate for a true apples-apples comparison. See both: https://www.onehouse.ai/blog/apache-hudi-vs-delta-lake-transparent-tpc… and https://github.com/brooklyn-data/delta/pull/2
joeharris76 · 2023-01-11
"A grand don't come for free"
It's interesting that they link to (and show graphs from) their earlier post but fail to mention that they had to disable a very large chunk of the features in the checklist to get that performance.
Their earlier post: https://www.onehouse.ai/blog/apache-hudi-vs-delta-lake-transparent-tpc…
Responding to: https://databeans-blogs.medium.com/delta-vs-iceberg-vs-hudi-reassessin…
cosmicgadget · 2025-04-25
What If We Could Rebuild Kafka From Scratch? - Gunnar Morling (https://news.ycombinator.com/item?id=43790420)
1. Five Advantages of Log-Based Change Data Capture (https://debezium.io/blog/2018/07/19/advantages-of-log-based-change-dat…
2. Why Data Architecture Should Guide Your Query Engine Decision (https://www.onehouse.ai/blog/why-data-architecture-should-guide-your-q…
3. Reimagine Apache Kafka (https://streamnative.io/blog/ursa-reimagine-apache-kafka-for-the-cost-…
4. Book Review: Designing Data-Intensive Applications | Henrik Warne's blog (https://henrikwarne.com/2019/07/27/book-review-designing-data-intensiv…
5. Of Streams and Tables in Kafka and Stream Processing, Part 1 (https://www.michael-noll.com/blog/2018/04/05/of-stream-and-tables-in-k…