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7x faster Iceberg ingestion, how we redesigned OLake's writer

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OLake is our open-source tool for ingesting Database & Kafka data into Apache Iceberg. We recently redesigned the write pipeline and saw ~7x throughput improvements. Sharing the architecture decisions, trade-offs, and benchmarks.

HN · launched Dec 5, 2025 · 5 upvotes (top 90%) · 0 views

Niche: specialized algorithms and computing libraries · 230 launches, 4 in the last 7 days ▼ -73% · Explore this niche →

Category and tags

  • Horizontal
  • Data infrastructure
  • B2B
  • Not AI
  • Commercial product

Visit website ↗ Source listing ↗

Could you build this?

No Redesigning an ultra-high-throughput ingestion pipeline for Apache Iceberg and Kafka requires deep database internals, concurrency engineering, and low-level data lake format expertise.

What it would actually take: The system requires an optimized Go or Rust engine interfacing directly with Apache Iceberg metadata specifications, parquet writing, and Kafka/CDC consumers. The core challenge lies in high-concurrency buffering, zero-copy serialization, atomic multi-partition commits, and exactly-once semantics without introducing file-compaction thrashing. This demands senior distributed systems and data engineering expertise.

Discussion

1 comment analyzed.

Competitors mentioned: Apache Airflow, Kafka, dbt, Fivetran

Concerns raised: Memory usage scaling (44-59 GB on 128 GB VM), Benchmark fairness (comparing against unnamed alternative tools), Production stability at scale, Real-world constraint handling

Feature requests: S3/GCS/HDFS ingestion optimization details, Schema evolution best practices documentation, Multi-source parallel ingestion, Dead letter queue handling for failed records

Competitors

Other products that read as similar to this one : 72 launches clear the similarity bar, closest 8 shown.

Attention rank: #71 of 73 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 37 days after the earliest competitor.

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