A cloud-native Write-Ahead Log storage engine that leverages object storage for ultra-low cost, high throughput, and geo-distributed durability.
Every component of Woodpecker is built from the ground up for cloud-native infrastructure, delivering the reliability and performance your systems demand.
Uses cloud object storage (S3, GCS, Azure, OSS) as the durable layer, decoupling compute from storage for infinite scalability and zero capacity planning.
Designed for multi-region deployments with cross-geo replication support. Leverage cloud provider's built-in geo-redundancy for global data durability.
Achieves 60-80% of maximum storage backend throughput. Up to 750MB/s on S3 and 450MB/s on local storage with optimized batching and async writes.
Deploy as a standalone service with dedicated LogStore cluster, or embed directly as a library in your application. Choose what fits your architecture.
Novel quorum-based replication with configurable ensemble size, write quorum, and ack quorum. Supports affinity-aware node selection and AZ-aware placement.
Minimal dependencies with etcd for metadata. Pluggable storage backends, Prometheus metrics, OpenTelemetry tracing, and condition-write fence mechanism built in.
Choose the deployment model that matches your performance and operational requirements.
A lightweight library integrated directly into your application with minimal operational overhead. Only requires etcd for coordination.
A dedicated LogStore cluster acts as a high-performance caching layer between clients and object storage, maximizing throughput and minimizing latency.
Single-node, single-client, single-log-stream benchmark results compared to industry standards.
Initially built for Milvus vector database and Zilliz Cloud, with strong potential across diverse cloud workloads.
Ensure write-ahead logging with strict ordering and persistence for distributed databases. Seamlessly replaces on-prem WAL solutions.
Provide a durable, ordered event log for stream processing frameworks with cloud-native scalability and cost efficiency.
Serve as a persistent log backend for distributed consensus algorithms like Raft and Paxos, with built-in quorum support.
Store ordered, durable logs for financial or critical business applications with strict consistency guarantees and multi-cloud support.
Get started with just a few lines of Go code. Woodpecker's clean API abstracts away the complexity of distributed log storage.
// Create an embedded client cfg, _ := config.NewConfiguration() client, _ := woodpecker.NewEmbedClientFromConfig(ctx, cfg) // Create and open a log client.CreateLog(ctx, "my-wal") logHandle, _ := client.OpenLog(ctx, "my-wal") // Open a writer writer, _ := logHandle.OpenLogWriter(ctx) // Async write with properties result := writer.WriteAsync(ctx, &log.WriteMessage{ Payload: []byte("hello world"), Properties: map[string]string{ "key": "value", }, }, ) writeResult := <-result // Open a reader and iterate reader, _ := logHandle.OpenLogReader(ctx, start) for { msg, err := reader.ReadNext(ctx) if err != nil { break } process(msg.Payload) }
Seamlessly integrates with your existing cloud infrastructure and monitoring stack.
Deploy Woodpecker in minutes and start building cloud-native log infrastructure.