Rare: a table-formats article that doesn't tell you to rip-and-replace everything for Iceberg. If you work near a lakehouse, it's worth a read. Key points, regardless of what you run: 💸 The format itself costs $0. Iceberg, Delta, and Hudi are Apache-2.0. You pay for compute, storage, and the platform—so the real question is engine economics for your workload.

🧬 They came from different problems, and that still shows: Iceberg (Netflix append analytics), Delta (Spark/Databricks), Hudi (Uber streaming + frequent updates). 🔄 In Databricks and Fabric, Delta is effectively an optimized, Iceberg-compatible path. With UniForm, it can present an Iceberg interface, and is often cheaper/easier than "rolling your own Iceberg." "Move everything to Iceberg" is often a fake mandate.

⚡ For heavy writes (upserts/CDC/high-frequency ingestion), Hudi remains the purpose-built option: indexing, merge-on-read, non-blocking concurrency. The calming part: this isn't the warehouse era where you need to make a hard choice between "open" and "closed". Tools like Apache XTable (incubating) and UniForm make "format" mostly a metadata choice, not a data migration. Write in what fits your write path, expose others for reads—no copy, no rewrite.

So the sane default isn't "pick the winner." It's: match the format to your dominant workload, translate metadata instead of rewriting data, and keep your options open — because these formats are interoperable in a way warehouses never were or even are. (Disclosure: I started Hudi.)

Article: tech-insider.org/apache-iceberg…