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With mirror pipelines, you can access to indexed on-chain data. Define them as a source and pipe them into any sink we support.

Use-cases

  • Mirror specific logs and traces from a set of contracts into a postgres database to build an API for your protocol
  • ETL data into a data warehouse to run analytics
  • Push the full blockchain into Kafka or S3 to build a datalake for ML

Supported Chains

Every EVM chain listed below is also supported on Turbo pipelines with the same datasets and schemas. Turbo additionally supports Solana, Bitcoin, Stellar, and NEAR. See Mirror vs. Turbo for a full comparison.

EVM chains

For EVM chains we support the following 4 datasets:

Fast Scan

Some datasets have support for Fast Scan which allows you to more quickly backfill filtered data. If a chain has partial support for Fast Scan, the dataset that doesn’t support fast scan will have an asterisk * next to it. Here’s a breakdown of the EVM chains we support and their corresponding datasets: * The Arweave dataset includes bundled/L2 data.

Non-EVM chains

Beacon

Fogo

IOTA

Movement

NEAR

NEAR datasets are no longer available through Mirror. Use Turbo pipelines for NEAR data.

Solana

Solana datasets are no longer available through Mirror. Use Turbo pipelines for Solana data.

Starknet

Stellar

Stellar datasets are no longer available through Mirror. Use Turbo pipelines for Stellar data.

Sui

Curated Datasets

Beyond onchain datasets, the Goldsky team continuosly curates and publishes derived datasets that serve a specific audience or use case. Here’s the list:

Token Transfers

You can expect every EVM chain to have the following datasets available:

Polymarket datasets

Additional chains, including roll-ups, can be indexed on demand. Contact us at sales@goldsky.com to learn more.

Schema

The schema for each of these datasets can be found here.

Backfill vs Fast Scan

Goldsky allows you either backfill the entire datasets or alternatively pre-filter the data based on specific attributes. This allows for an optimal cost and time efficient streaming experience based on your specific use case. For more information on how to enable each streaming mode in your pipelines visit our reference documentation.