Catalogue/Dev tools/Mako

Mako

Real-time data pipelines, described in YAML.

A declarative framework for orchestrating data pipelines. Describe your sources, transformations and destinations in YAML: Mako handles execution, monitoring and alerting.

View the repoGitHub
MITLicense
Go 1.21+Runtime
Real-timeCategory
Open sourceStatus
Inside this edition

Data in motion, without the glue.

No.01

Declarative

Everything is configured in YAML. No code to write for standard pipelines.

No.02

Real-time

Native support for Kafka, PostgreSQL CDC and HTTP streaming.

No.03

WASM transforms

Go, Rust or TinyGo plugins compiled to WebAssembly for fast transformations.

No.04

Observability

Built-in Prometheus metrics, Grafana dashboards and Slack alerts.

Why Mako?

Moving data from point A to point B looks simple, until you have to handle pagination, CDC, schema validation, PII masking and alerting. Most teams end up writing and maintaining mountains of plumbing code.

Mako replaces that code with a YAML file. Sources, transformations, destinations: all declared, versioned, reviewable. Heavy transformations run through WebAssembly plugins, and Prometheus observability is built in. MIT licensed, built for production.

In brief
What is Mako?

Mako is an open-source framework for real-time data pipelines, configured in YAML. It connects sources (Kafka, PostgreSQL CDC, HTTP APIs), applies WebAssembly transformations and writes to destinations like Snowflake, BigQuery or ClickHouse. Prometheus observability and Slack alerts are built in. MIT licensed.

Frequently asked

Everything people ask us.

Is Mako a Kafka Streams, Flink or Airflow alternative?
Mako sits between Kafka Streams or Flink (streaming) and Airflow or Dagster (DAGs). It defines real-time pipelines in YAML with WASM transforms and Prometheus observability, under an MIT license.
Which sources does Mako support?
Kafka, Change Data Capture (Postgres, MySQL) and HTTP as sources; WASM transformations; configurable destinations (Snowflake, BigQuery, ClickHouse, S3 and more).
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Describe your pipeline.

Open source, MIT licensed. One YAML file, and Mako handles the rest.

View the repoGitHub

In brief

How does Mako orchestrate a real-time data pipeline?

Mako is an open-source Go framework that describes real-time data pipelines as declarative YAML files, with no code. A Mako pipeline has 3 sections: sources (Kafka, Change Data Capture on Postgres or MySQL, HTTP endpoints), transforms (WASM modules compiled from Rust, Go, or Python), and sinks (Kafka, S3, relational database, webhook). At runtime, Mako builds a directed acyclic graph (DAG) in memory and applies automatic backpressure between stages — if a sink is slow, the sources slow down without saturating memory. Mako exposes 14 standard Prometheus metrics (throughput, p50/p95/p99 latency, queue sizes, errors per stage) and ships with a reference Grafana dashboard. The binary is under 30 MB and starts in under 200 ms.

How does Mako differ from Kafka Streams and Airflow?

Kafka Streams is a Java library for streaming inside a JVM, tightly coupled to Kafka. Airflow and Dagster orchestrate scheduled batch jobs, not continuous streaming. Mako sits in the middle: it handles continuous streaming like Kafka Streams or Apache Flink, but with a declarative YAML definition — no Java compilation required — and a standalone Go binary that runs on a bare server, in a Kubernetes container, or on an edge node. WASM transforms let teams write business logic in Rust, Go, AssemblyScript, or compiled Python without recompiling the engine. Mako is distributed under the MIT license on GitHub and is designed for teams of 1 to 5 engineers who do not want to operate a full Flink cluster.

Frequently asked questions

Is Mako a Kafka Streams, Flink or Airflow alternative?

Mako sits between Kafka Streams/Flink (streaming) and Airflow/Dagster (DAGs). It defines real-time pipelines in YAML with WASM transforms and Prometheus observability, under MIT license.

Which sources does Mako support?

Kafka, Change Data Capture (Postgres, MySQL) and HTTP as sources; WASM transforms; configurable sinks.

Mako — Real-Time Data Pipeline Framework | mcsÉdition