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Polaris is a market data platform for frontier venues across crypto derivatives, RWAs, and compute markets. It gives you one place to discover supported venues, inspect exact market identifiers, download historical files, and query recent market activity without rebuilding venue-specific ingestion from scratch.

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What Polaris is

Use Polaris when you need to:
  • Discover which venues, markets, and time ranges are available right now.
  • Download historical snapshot files for bulk research and ingestion.
  • Query recent trades, events, and OHLCV bars over REST.
  • Inspect raw venue-native payloads when replayability matters.
  • Reuse the same access model across the CLI, REST API, and SDKs.

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Why teams use Polaris

Most market data work breaks down at the venue layer. Every venue has its own identifiers, timestamp conventions, payload shapes, and quirks around history. Polaris gives you one place to:
  • Browse coverage before you build.
  • Start with public access, then add authentication only when you need more.
  • Choose the right surface for the job: CLI, snapshots, REST, raw payloads, or SDKs.
  • Move between venues without rewriting your entire parsing pipeline.

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Choose your path

Quickstart

Install the Polaris Python SDK and query your first market data.

Market Coverage

Browse supported venues, preview and open access tiers, and example market IDs.

Python SDK

Use polaris_data to discover markets, fetch datasets, and replay data locally.

TypeScript SDK

Use polaris-data in Node.js to load events, trades, and OHLCV bars.

Rust SDK

Use polaris-data in Tokio services and backfills with streaming queries.
  1. Start with Quickstart if you want the fastest route to first data.
  2. Open Market Coverage to browse supported venues and their access tiers.
  3. Use Catalog to confirm exact source and market pairs.
  4. Pick an SDK for application code, or use Snapshots when you need bulk historical files.

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Typical workflows

  • Use the CLI when you want the fastest path to browsing and downloading data.
  • Use snapshots when you need bulk historical files for research, backfills, or ingestion.
  • Use REST when you want recent trades, events, or OHLCV bars on demand.
  • Use raw payloads when you need venue-native fields for replay or validation.
  • Use an SDK when you want a notebook, local analysis, or production workflow.

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Support and resources

  • Use Market Coverage for a live high-level view of currently listed venues.
  • Use Jupyter Notebook if you want a notebook-first Python workflow.
  • Use Quickstart to install the SDK and add an API key when you need broader access.