Benthos Stream Processing Framework

Benthos is a free and open-source stream processing framework that enables declarative data transformation and routing between various input and output systems without requiring custom code. Originally created by Jeffail (Ashley Jeffs) in 2017 and now part of the Benthos project (acquired by RedPanda Data in 2023, headquartered in San Francisco), Benthos is designed as a high-performance, resilient stream processor that treats data pipelines as configuration rather than code. Key features: declarative configuration: all data pipelines are defined in YAML configuration files, specifying inputs, processors, outputs, and rate limits without writing any code. Input types: HTTP (server and client), Kafka, Amazon SQS, Amazon S3, Amazon Kinesis, Amazon DynamoDB, GCP Pub/Sub, NATS, NATS JetStream, NSQ, Redis, MQTT, NATS, AMQP (RabbitMQ), WebSocket, file (reading from local or remote files), SQL Select (polling databases), CSV, read_until, inproc, nanomsg, Pulsar, and stdin. Output types: matching inputs plus Elasticsearch, MongoDB, Cassandra, HDFS, and custom HTTP endpoints. Processors: over 50 built-in processors for data transformation including JSON manipulation (jq queries, mapping, filtering), text manipulation (regex, split, replace), batching, compression (gzip, zlib, snappy, lz4), encoding/decoding (base64, hex, avro, protobuf), HTTP requests, SQL Insert/Update/Delete, caching, rate limiting, branching logic (switch, try, catch), parallel processing, and schema validation. Buffer and retry mechanisms: in-memory and file-based buffers for backpressure handling, with automatic retries and dead letter queues. Observability: Prometheus metrics, OpenTelemetry tracing, and structured JSON logging. Cross-platform binaries for Linux, macOS, Windows. Over 100 components. Deployable as standalone binary, Docker container, or Kubernetes sidecar. MIT (community edition).