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DuckDB for Kafka Stream Processing

Details

External ID
46195007
Source
HN
Company
—
Product
DuckDB for Kafka Stream Processing
Website domain
sql-flow.com
Launched
Dec. 8, 2025
Cohort
—
Upvotes
77
Upvotes percentile
0.8625954198473282
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hello Everyone! We built SQLFlow as a lightweight stream processing engine.We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory!DuckDB also supports a rich ecosystem of sinks and connectors!https://sql-flow.com/docs/category/tutorials/https://github.com/turbolytics/sql-flowWe were tired of running JVM's for simple stream processing, and also of bespoke one off stream processorsI would love your feedback, criticisms and/or experiences!Thank you

Enrichment

Theme
database infrastructure and developer tools
Vertical
Horizontal
Function
Data infrastructure
Audience
Developer
AI stance
Not AI
Project type
Hobby / open-source project
Normalized one-liner
stream processing with duckdb and kafka
Manually corrected
False

Could you build this?

No Building a stream processing engine integrating Kafka with embedded DuckDB at 10,000+ msgs/sec in a tiny memory footprint requires deep low-level systems and streaming engine internals expertise.

What it would actually take: The engine is likely built in Rust or Go, embedding DuckDB via C/FFI bindings, with custom streaming buffer management, Kafka consumer group rebalancing, tumbling/sliding window aggregation logic, and exactly-once/at-least-once sink delivery. The difficult parts are zero-copy buffer handoffs, backpressure handling, stateful stream crash-recovery, and high-throughput low-latency memory management.

Discussion

13 comments analyzed.

Competitors mentioned: Tributary, Flink, Snowflake, BigQuery, SQLite

Concerns raised: Unclear production-readiness and operational deployment story, Batch processing vs. true streaming semantics unclear, Lacks DevOps, testing, configuration-as-code tooling, Stream-to-stream joins not supported, Feels hacky for continuous streaming use cases

Feature requests: Stream-to-stream joins support, Apache Pulsar support (in addition to Kafka), Avro and Protobuf schema support, Kafka transactions for writes, Materialized views for streaming aggregates

Competitors

Other products that read as similar to this one — 108 launches clear the similarity bar, closest 8 shown.

Attention rank: #17 of 109 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 40 days after the earliest competitor.

Other launches for this product

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