faucet-stream vs. Redpanda Connect (Benthos)
The other declarative-YAML single binary. Here’s where each one wins — including an honest note on the license history.
The short version
Section titled “The short version”Redpanda Connect is the tool formerly known as Benthos (acquired by Redpanda in 2024) — a Go stream processor configured with declarative YAML (input → processors → output). It’s streaming-first, has a large component library, and is the closest architectural analogue to faucet-stream’s config-driven model. Ships as a single binary or as managed pipelines on Redpanda Cloud.
faucet-stream is built for batch/ELT data movement rather than continuous stream processing: incremental + resumable replication, snapshot→CDC, first-class warehouse sinks, and governance in the movement path — under uniform permissive licensing.
Reach for Redpanda Connect for continuous, record-by-record streaming; reach for faucet-stream to move data between databases, object stores, and warehouses as discrete, resumable, governed runs.
A note on licensing
Section titled “A note on licensing”Worth stating precisely, because it’s a real adoption consideration: Benthos was originally MIT. After the Redpanda acquisition the maintained repo moved to a mix of Apache-2.0 and a source-available Redpanda Enterprise/Community license, with some components (certain CDC inputs and others) gated behind the enterprise license. The community forked the pre-relicensing project as Bento, which continues under permissive terms. faucet-stream is uniformly MIT / Apache-2.0 with no enterprise-gated connectors.
Where faucet-stream is different
Section titled “Where faucet-stream is different”- Batch/ELT is the home turf. Incremental + resumable replication, snapshot→CDC handoff, and first-class warehouse sinks (BigQuery, Snowflake, Iceberg, Delta) — the job faucet is built for.
- Governance in the movement path. Data-quality checks, versioned data contracts, PII masking (before any sink sees a row), schema-drift policy, column-level lineage (OpenLineage) + a catalog, and freshness/volume SLAs — native and zero-config.
- Effectively-once delivery. Per-page commit tokens commit atomically with the data, so a resumed run drops duplicates — across 13 sinks (SQL, Oracle, Kafka, Iceberg, BigQuery, Snowflake, Spanner, Databricks, MongoDB, Redis).
- Uniform permissive licensing. MIT / Apache-2.0 throughout — no per-component enterprise gate to audit.
Where Redpanda Connect is the better choice
Section titled “Where Redpanda Connect is the better choice”Straight with you — for its core job it’s excellent:
- Continuous, record-by-record streaming. It’s purpose-built for never-ending stream processing with a rich processor/transform library. faucet runs discrete pipelines to completion — even its long-running modes (
faucet schedule,faucet serve) orchestrate complete runs, not an endless stream. - Deep Redpanda/Kafka ecosystem integration and a large, mature component catalog.
- Battle-tested across years of production stream-processing use, with a Go library you can embed.
Side-by-side
Section titled “Side-by-side”| faucet-stream | Redpanda Connect (Benthos) | |
|---|---|---|
| Language / runtime | Rust, single binary | Go, single binary |
| Orientation | discrete runs to completion | continuous stream processing |
| Connectors | 78 source/sink, ETL/CDC/warehouse | hundreds of components/processors |
| Change data capture | ✓ engine-level | some CDC inputs (several enterprise-gated) |
| Warehouse / ELT sinks | ✓ BigQuery, Snowflake, Iceberg, Delta, … | more messaging/stream-oriented |
| Governance in-path (quality / contracts / masking / lineage / SLA) | ✓ native | ✗ |
| Effectively-once delivery | ✓ (13 sinks incl. Kafka, Iceberg, BigQuery, Databricks, Oracle) | ✗ |
| Embeddable as a library | ✓ (Rust) | ✓ (Go) |
| License | MIT / Apache-2.0 | Apache-2.0 + source-available enterprise |
Rule of thumb
Section titled “Rule of thumb”If the workload is a continuous stream you transform in flight, Redpanda Connect is purpose-built for it. If the workload is moving data between APIs, databases, object stores, and warehouses as discrete, resumable, governed runs — see replication (snapshot → CDC) — that’s faucet-stream.
See for yourself
Section titled “See for yourself”- Choosing a connector — confirm your sources and sinks are covered.
- Try it in 60 seconds — no infrastructure needed.
- Benchmarks — full methodology and honest caveats.