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Hudi 1.0 is the most powerful release to date for data lakehouses. Read the blog for details:
Secondary Indexing, Expression Indexes, Partial Updates, Non-blocking Concurrency Control, New LSM timeline, +more: hudi.apache.org/blog/2024/12…
#datalakehouse #opentableformat
• hoodie.memory.merge.fraction — bump if upserts spill to temp folder
• Timeseries / log data — tune bloom accuracy OR use bucket index; time-prefix keys for range pruning
Links ↓
#ApacheHudi #SparkTuning
Tuning guide docs: hudi.apache.org/docs/tuning-…
Indexes overview: hudi.apache.org/docs/indexes
Zendesk ran CDC from 1,800+ Aurora MySQL databases across 8 AWS regions into one Apache Hudi data lake.
10+ billion ticket events. Petabytes of data ↓
Cross-region, multi-database CDC at meaningful scale.
Links ↓
#ApacheHudi #CDC
AWS Architecture Blog (co-authored with Johnathan Hwang, Zendesk): aws.amazon.com/blogs/archite…
Unsafe (workarounds required): non-nullable column (make it nullable), datatype demotion (rewrite), field reorder (breaks partial-coverage upsert reads).
For column renames + deletes + complex evolution: opt into schema-on-read with hoodie.schema.on.read.enable=true. Spark 3.2.1+, can't be disabled once on.
Proven at scale at Uber, Walmart, LinkedIn.
Links ↓
#ApacheHudi #SchemaEvolution
Schema evolution docs: hudi.apache.org/docs/schema_…
Mastering Schema Evolution blog: hudi.apache.org/blog/2025/12…
Upstream added a column. Did your pipeline survive?
Hudi supports schema evolution on write out of the box — the changes that happen in production all the time.
Upstox — one of India's largest online trading platforms — ingested 300 GB of new data per day for 12 million customers on Apache Hudi.
Capital markets workloads stress every part of a lakehouse ↓
Streaming-first lakehouse, built for upserts on S3 — what trading-day workloads require. 300k data requests served daily.
Links ↓
#ApacheHudi #FinTech
Upstox engineering blog hudi.apache.org/blog/2025/10…
Hudi concurrency control: hudi.apache.org/docs/next/co…




