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Ankur Kumar Pandey reports that rekuiper, a Rust rewrite of LF Edge eKuiper, processed a 500,000-event telemetry workload at 425,308 events per second, using about 8 MB of memory with no reported drops. Those figures come from one author-run test on WSL2 / Ubuntu x86_64—not an independent benchmark or a physical edge-device test. The headline’s “13 ms boot” refers to internal daemon bootstrap; the same article reports 123 ms from process spawn to a ready socket.
What was tested—and what the numbers mean
In a September 10, 2026 DEV Community article, Ankur Kumar Pandey describes rekuiper v0.421-beta, a Rust rewrite of LF Edge eKuiper for local telemetry stream processing. The test used 500,000 JSON events and, according to the article, ran each engine on the same WSL2 / Ubuntu x86_64 machine.
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The described pipeline parsed each event, calculated temp * 1.8 + 32, filtered on temp > 20.0, projected id and temp_f, and sent results to a sink. The figures below are all reported by the article’s author; they have not been independently reproduced.
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|---|---|---|---|---|---|
| rekuiper 0.421 | Rust | 1.176 s | 425,308 events/sec | 0 (0.0%) | about 8 MB |
| Apache Flink | Java / JVM | 2.144 s | 233,209 events/sec | 0 (0.0%) | about 1,022 MB |
| Telegraf | Go | 8.194 s | 61,019 events/sec | 0 (0.0%) | about 50 MB |
| Upstream Go eKuiper | Go | 11.290 s | 44,287 events/sec | 72,921 (14.6%) | about 45 MB |
| Redpanda Connect | Go | 19.236 s | 25,993 events/sec | 0 (0.0%) | about 38 MB |
In this particular test, rekuiper had the highest reported throughput and lowest reported memory use; it and three other entries recorded no drops, while upstream Go eKuiper was reported to drop 72,921 events. That is a result for the stated batch workload and environment, not evidence that rekuiper will be faster or smaller for every stream-processing job.
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Why the benchmark needs context
A single workload cannot establish how an engine will behave with different event sizes, stateful queries, sustained input, production traffic, or downstream bottlenecks. The article does not report a physical Raspberry Pi, Advantech gateway, or embedded ARM test, nor does it establish long-duration stability or recovery after network failures.
The author attributes upstream eKuiper’s reported drops to Go-channel saturation and describes rekuiper’s queues and architecture as the explanation for its behavior. These are the author’s interpretation of the results; the benchmark does not independently verify that causal explanation. For a useful comparison in your own environment, measure throughput, memory, drops, and latency using the same workload and configuration, and record the hardware and operating environment.
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What “13 ms boot” measures
The headline’s approximately 13 ms figure is the article’s reported internal daemon bootstrap time, given as a 12.5–14.5 ms range. It is not the full time from launching the operating-system process to being ready for connections: the article reports 123 ms for process spawn to ready socket. Keep those two timing definitions separate when assessing whether startup is fast enough for your application.
What the Rust rewrite claims to include
The article describes rekuiper as using a lock-free StreamBus, Tokio asynchronous actors for rule execution, bounded sink queues, and no runtime garbage collector. It also claims compatibility with the eKuiper Manager Web UI, OpenAPI 3.0 schemas, standard streaming SQL, and 98 REST endpoints. Those are claims in the project author’s account; the available article details do not independently establish implementation parity or compatibility for a particular release.
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The author situates the project in local telemetry processing—SQL filtering, sliding windows, and MQTT or Kafka sinks—on edge devices including Raspberry Pi boards, Advantech gateways, and embedded x86/ARM systems. The benchmark itself does not show results from those devices. Since the tested version is identified as v0.421-beta, verify that the exact capabilities and interfaces you need are present in the version you plan to use.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to use the result when choosing a stream processor
- Use the figures as a lead, not a forecast. They indicate what the author observed on one WSL2 / Ubuntu x86_64 test, not expected performance on other hardware.
- Match the workload. Reproduce the event shape, calculation, filter, projection, and sink behavior that matter to your application.
- Track data loss as well as speed. The reported upstream Go eKuiper result illustrates why throughput alone can be misleading when records are dropped.
- Separate startup measurements. Compare internal initialization with full process-to-ready time only against measurements defined the same way.
- Validate operational behavior. Test sustained operation, realistic sinks, failures, and recovery before relying on a beta engine in production.
Read the original author’s report for its benchmark details: Ankur Kumar Pandey’s rekuiper benchmark on DEV Community.
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