Developer toolkit for building real-time analytical backends in Typescript and Python — MooseStack brings data engineering best practices and a modern web development DX to any engineer building on data infra.
MooseStack modules offer a type‑safe, code‑first developer experience layer for popular open source analytical infrastructure, including ClickHouse, Kafka, Redpanda, and Temporal.
MooseStack is designed for:
- Software engineers integrating analytics & AI into their apps, and leaning into real-time / OLAP infrastructure best practices
- Data engineers building software & AI applications on their data infra, and leaning into software development best practices
- Git-native development: Version control, collaboration, and governance built-in
- Local-first experience: Full mirror of production environment on your laptop with
moose dev - Schema & migration management: typed schemas in your application code, with transparent migration support
- Code‑first infrastructure: Declare tables, streams, workflows, and APIs in TS/Python -> MooseStack wires it all up.
- Modular design: Only enable the modules you need. Each module is independent and can be adopted incrementally.
- AI copilot friendly: Designed from the ground up for LLM-powered development
- Moose OLAP: Manage ClickHouse tables, materialized views, and migrations in code.
- Moose Streaming: Real‑time pipelines with Kafka/Redpanda and transformation functions.
- Moose Workflows: ETL pipelines and tasks with Temporal.
- Moose APIs: Type‑safe ingestion and query endpoints with auto‑generated OpenAPI docs.
- MooseStack Tooling: Moose Deploy, Moose Migrate, Moose Observability
Also available in the Docs: 5-minute Quickstart
Already running Clickhouse: Getting Started with Existing Clickhouse
bash -i <(curl -fsSL https://fiveonefour.com/install.sh) moose# typescript
moose init my-project --from-remote <YOUR_CLICKHOUSE_CONNECTION_STRING> --language typescript
# python
moose init my-project --from-remote <YOUR_CLICKHOUSE_CONNECTION_STRING> --language pythoncd my-project
moose devMooseStack will start ClickHouse, Redpanda, Temporal, and Redis; the CLI validates each component.
The easiest way to deploy your MooseStack Applications is to use Boreal from 514 Labs, the creators of Moose. Boreal provides zero-config deployments, automatic scaling, managed or BYO infrastructure, monitoring and observability integrations.
Moose is open source and can be self-hosted. For detailed self-hosting instructions, see our deployment documentation.
import { Key, OlapTable, Stream, IngestApi, ConsumptionApi } from "@514labs/moose-lib";
interface DataModel {
primaryKey: Key<string>;
name: string;
}
// Create a ClickHouse table
export const clickhouseTable = new OlapTable<DataModel>("TableName");
// Create a Redpanda streaming topic
export const redpandaTopic = new Stream<DataModel>("TopicName", {
destination: clickhouseTable,
});
// Create an ingest API endpoint
export const ingestApi = new IngestApi<DataModel>("post-api-route", {
destination: redpandaTopic,
});
// Create consumption API endpoint
interface QueryParams {
limit?: number;
}
export const consumptionApi = new ConsumptionApi<QueryParams, DataModel[]>("get-api-route",
async ({limit = 10}: QueryParams, {client, sql}) => {
const result = await client.query.execute(sql`SELECT * FROM ${clickhouseTable} LIMIT ${limit}`);
return await result.json();
}
);from moose_lib import Key, OlapTable, Stream, StreamConfig, IngestApi, IngestApiConfig, ConsumptionApi
from pydantic import BaseModel
class DataModel(BaseModel):
primary_key: Key[str]
name: str
# Create a ClickHouse table
clickhouse_table = OlapTable[DataModel]("TableName")
# Create a Redpanda streaming topic
redpanda_topic = Stream[DataModel]("TopicName", StreamConfig(
destination=clickhouse_table,
))
# Create an ingest API endpoint
ingest_api = IngestApi[DataModel]("post-api-route", IngestApiConfig(
destination=redpanda_topic,
))
# Create a consumption API endpoint
class QueryParams(BaseModel):
limit: int = 10
def handler(client, params: QueryParams):
return client.query.execute("SELECT * FROM {table: Identifier} LIMIT {limit: Int32}", {
"table": clickhouse_table.name,
"limit": params.limit,
})
consumption_api = ConsumptionApi[RequestParams, DataModel]("get-api-route", query_function=handler)Already running Clickhouse? MooseStack gives you a modern software DX on your existing ClickHouse or ClickHouse Cloud cluster: Getting Started with Existing Clickhouse
bash -i <(curl -fsSL https://fiveonefour.com/install.sh) moose# typescript
moose init my-project --from-remote <YOUR_CLICKHOUSE_CONNECTION_STRING> --language typescript
# python
moose init my-project --from-remote <YOUR_CLICKHOUSE_CONNECTION_STRING> --language pythoncd my-project
moose devMooseStack will start ClickHouse, Redpanda, Temporal, and Redis; the CLI validates each component.
The easiest way to deploy to production with MooseStack is to use Boreal from Fiveonefour, the creators of MooseStack. Boreal provides github integration for CI/CD and one click deploys, cloud previews of your dev branches, managed or BYO infrastructure, and security + observability. Boreal works natively with ClickHouse Cloud and RedPanda Cloud.
MooseStack is open source, and apps built with MooseStack can be self-hosted. For detailed self-hosting instructions, see our deployment documentation.
- ClickHouse (OLAP storage)
- Redpanda (streaming)
- Temporal (workflow orchestration)
- Redis (internal state)
MooseStack works with Cursor's background agents for remote development. The repository includes a pre-configured Docker-in-Docker setup that enables Moose's Docker dependencies to run in the agent environment.
- Enable background agents in Cursor
- The environment will automatically build with Docker support
- Run
moose devor other Moose commands in the agent
For detailed setup instructions and troubleshooting, see Docker Setup Documentation.
We welcome contributions! See the contribution guidelines.
MooseStack is open source software and MIT licensed.