At a Glance:
Trench is an open-source event tracking infrastructure built on Kafka and ClickHouse that provides a Segment API–compatible interface, real-time querying, and single-node processing of thousands of events per second.
Overview:
Trench is an open-source analytics infrastructure for capturing and querying event data at scale. It provides a Segment-compatible API for tracking, grouping, and identifying users, while running on a stack that combines Apache Kafka and ClickHouse for event handling and real-time analytics. Trench supports self-hosted deployment through a single Docker Compose setup and a managed cloud option, with querying available through an events endpoint and direct SQL access. The system can process thousands of events per second on a single node and offers webhooks for routing data to other destinations. It is designed for teams that need a data pipeline they can control and inspect.
Key Decision Points:
Self-hosted or cloud deployment: Trench can be deployed as a self-managed Docker instance or used as a fully managed cloud service with zero ops and autoscaling.
Segment API compatibility: It implements the Segment API subset for Track, Group, and Identify calls, making it suitable for existing Segment instrumented workflows.
Real-time SQL querying: Users can execute raw SQL queries directly against event data through the built-in queries endpoint, enabling custom analysis without additional tooling.
Kafka authentication support: Trench can connect to Kafka clusters requiring SASL and SSL, with configuration options for client certs, CA certs, and multiple SASL mechanisms.
Event throughput: A single node can process thousands of events per second, making it relevant for high-volume yet self-contained analytics pipelines.
Core Features:
Segment-compatible API: Accepts Track, Group, and Identify calls, allowing reuse of existing Segment event instrumentation.
Single-image Docker deployment: The system starts from one production-ready Docker image, including local Kafka and ClickHouse instances.
Real-time event querying: Provides an
/eventsendpoint to retrieve submitted events immediately, with filtering by event type.Direct SQL access: A queries endpoint supports raw SQL execution against ClickHouse data for custom analytics and transformations.
Webhook-based data routing: Events can be forwarded to external destinations as they are processed.
Configurable Kafka authentication: Supports SASL mechanisms (PLAIN, SCRAM-SHA-256, SCRAM-SHA-512) and SSL/TLS for connecting to secured Kafka clusters.
Use Cases:
Developers migrating from Segment: Teams already using Segment client libraries can switch to Trench for self-hosted event collection without changing event instrumentation.
Self-hosted analytics pipelines: Organizations that need to process high-throughput event data on their own infrastructure can run Trench on a single node with Docker.
Real-time ad hoc analysis: Data teams can query event streams directly via SQL without needing separate analytical databases or ETL jobs.
Open-Source Alternative Value:
Trench offers an MIT-licensed event tracking pipeline that replaces the Segment API ingestion layer while giving developers full access to the underlying Kafka and ClickHouse components. Rather than sending event data to a third-party service, users can deploy the entire stack within their own environment using a single Docker setup. The availability of direct SQL querying and webhook-based routing means data teams can build custom analytics workflows on top of Trench without being constrained by a managed vendor interface, and the Segment‑compatible API reduces migration effort for existing setups.
