Load Apache NiFi Registry data to DuckDB

Apache NiFi Registry is a system for versioning and managing shared assets like NiFi flows, extension bundles, and configuration across multiple instances of Apache NiFi. Everything needed to build a working Apache NiFi Registry → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your Apache NiFi Registry to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Apache NiFi Registry to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Apache NiFi Registry API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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Apache NiFi Registry API at a glance

These values come from the Apache NiFi Registry API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Apache NiFi Registry API?

Access is authenticated via a Bearer token in the Authorization header. The token must be obtained first from the /access/token endpoint, typically using username/password credentials via HTTP Basic Auth.

1. Get your credentials

To obtain credentials for the Apache NiFi Registry REST API, you must exchange your primary credentials (such as username/password or custom identity tokens) for a JSON Web Token (JWT). Perform a POST request to the /access/token/login endpoint using HTTP Basic Authentication. The Authorization header should contain Basic <base64_encoded_username:password>. Upon successful authentication, the server returns a JWT. Use this token for subsequent authenticated requests by including it in the header as Authorization: Bearer . Note that some instances may require configuration in nifi-registry.properties to support username/password authentication.

2. Add them to .dlt/secrets.toml

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[sources.apache_nifi_registry_source]
nifi_registry_username = "your_username_here"
nifi_registry_password = "your_password_here"
nifi_registry_base_url = "https://your-registry-host:port"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What Apache NiFi Registry data can I load into DuckDB?

These are the Apache NiFi Registry endpoints dlt can load into DuckDB:

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How do I load only new Apache NiFi Registry records?

Apache NiFi Registry exposes none on buckets, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "buckets", "endpoint": {
    "path": "buckets",
    "data_selector": "none",
    "incremental": {"cursor_path": "none", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated Apache NiFi Registry pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /access/token/login and /buckets from the Apache NiFi Registry API into DuckDB:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def apache_nifi_registry_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "/nifi-registry-api",
            "auth": {"type": "bearer", "token": token},
        },
        "resources": [
            {"name": "buckets", "endpoint": {"path": "buckets", "data_selector": "none"}},
            {"name": "items", "endpoint": {"path": "items", "data_selector": "none"}}
        ],
    }
    yield from rest_api_resources(config)


def load_apache_nifi_registry_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="apache_nifi_registry_pipeline",
        destination="duckdb",
        dataset_name="apache_nifi_registry_data",
    )
    load_info = pipeline.run(apache_nifi_registry_source())
    print(load_info)


if __name__ == "__main__":
    load_apache_nifi_registry_to_duckdb()

Run it with python apache_nifi_registry_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query Apache NiFi Registry data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("apache_nifi_registry_pipeline").dataset()
df = data.buckets.df()
print(df.head())

SQL:

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SELECT * FROM apache_nifi_registry_data.buckets LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the Apache NiFi Registry to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw Apache NiFi Registry loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Apache NiFi Registry data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack