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Load Solana data to DuckDB

Build a Solana to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Solana API base URL, auth, endpoints, and incremental loading.

SourceSolanaSolana API DocumentationDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

Solana provides a JSON-RPC interface for reading blockchain state, submitting transactions, and subscribing to live events. Everything needed to build a working Solana → 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.


Build your Solana to DuckDB pipeline

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

Prompt
Run uvx dlthub-init@latest to build a pipeline from Solana 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 Solana 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.


Solana API at a glance

Base URLhttps://api.mainnet-beta.solana.com
Example endpointPOST /
Authenticationpublic endpoints are unauthenticated, while private RPC providers generally require API key authentication — sent in the request header
PaginationNot paginated
API referencehttps://solana.com/docs/rpc/http

These values come from the Solana API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Solana API?

The core Solana JSON-RPC protocol does not define an authentication mechanism; however, private RPC providers typically require an API key passed via the request header (e.g., 'x-api-key') or embedded directly in the request URL.

1. Get your credentials

To obtain an API key for Solana REST/RPC providers, sign in to your chosen provider's platform dashboard (e.g., Helius, OnFinality, or Solana Tracker). Navigate to the API keys or settings section, click 'New API key' (or similar), provide a name for the key, and save it immediately upon generation, as it is often displayed only once. Ensure the key is assigned the appropriate role (e.g., Read-only, Developer) and environment (e.g., Mainnet, Devnet) required for your pipeline.

2. Add them to .dlt/secrets.toml

[sources.solana_source] solana_api_key = "sk_prod_your_actual_key_here"

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.


What Solana data can I load into DuckDB?

These are the Solana endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
json_rpc_proxy/POSTThe primary interface for Solana is JSON-RPC 2.0 over HTTP. It uses a single endpoint for all methods.
health_check/healthGETHealth check endpoint returning status ('ok', 'behind', 'unknown').
mainnet_rpchttps://api.mainnet.solana.comPOSTPublic RPC endpoint for the mainnet cluster.
devnet_rpchttps://api.devnet.solana.comPOSTPublic RPC endpoint for the devnet cluster.
testnet_rpchttps://api.testnet.solana.comPOSTPublic RPC endpoint for the testnet cluster.

How do I load only new Solana records?

The Solana API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

{"name": "json_rpc_proxy", "endpoint": { "path": "/", # Replace with a field that increases on every write. "incremental": {"cursor_path": "REPLACE_ME", "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.


What does the generated Solana pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading mainnet and devnet from the Solana API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def solana_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.mainnet-beta.solana.com", "auth": {"type": "api_key", "api_key": api_key}, }, "resources": [ {"name": "json_rpc_proxy", "endpoint": {"path": "/"}}, {"name": "health_check", "endpoint": {"path": "/health"}} ], } yield from rest_api_resources(config) def load_solana_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="solana_pipeline", destination="duckdb", dataset_name="solana_data", ) load_info = pipeline.run(solana_source()) print(load_info) if __name__ == "__main__": load_solana_to_duckdb()

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


How do I query Solana 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):

import dlt data = dlt.pipeline("solana_pipeline").dataset() df = data.json_rpc_proxy.df() print(df.head())

SQL:

SELECT * FROM solana_data.json_rpc_proxy LIMIT 10;

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


How do I deploy the Solana 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 Solana loads into governed, documented models.
  • Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →


What other destinations can I load Solana data to?

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

DestinationExample value
PostgreSQL"postgres"
BigQuery"bigquery"
Snowflake"snowflake"
Redshift"redshift"
Databricks"databricks"
Filesystem (S3, GCS, Azure)"filesystem"

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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