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Export every covered Hyperliquid and Lighter market as a Parquet file with ZSTD compression, explicit schema keys, and UTC date ranges. 0xArchive Data Catalog exports turn that history into a durable dataset for research, backtesting, warehouse loads, and procurement. Pick a Parquet export when you need a reusable dataset, not a runtime response. The export carries the venue family, market slug, schema key, and date range with the file, so a table never loses whether it came from L2, L3, L4, trades, funding, OI, or liquidations.

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What One Catalog Returns

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Why Teams Choose 0xArchive

0xArchive exports come back as Parquet with ZSTD compression, keyed to explicit schemas and UTC ranges so coverage, cost, and warehouse partitioning stay reproducible. The Data Catalog keeps the buyer in the browser product flow while the docs keep the file contract distinct from JSON API responses. Schema keys stay separate, so l2_orderbook, l3_orderbook, l4_orderbook, l4_orders, trades, funding, oi, and liquidations never collapse into one namespace, and neither do Hyperliquid core, Spot, HIP-3, HIP-4, and Lighter. Lighter funding records are exportable where the catalog offers that schema, but currently served values must not be compared across venues or annualized pending normalization repair. Start from /data for the Data Catalog workflow. Use https://api.0xarchive.io/v1/symbols for machine-readable market discovery: the response has a top-level symbols array with rows that carry exchange, symbol, slug, data_types, and coverage fields. It tells a buyer which markets, schema data types, coverage windows, size estimates, active or delisted state, and HIP-4 outcome metadata are available before a single credit is spent. Venues outside Hyperliquid and Lighter, and workflows that need live streaming rather than bounded files, fall outside this export path.

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Selection Checklist

For Parquet exports, capture venue family, symbol-feed row, market slug, schema keys, UTC start and end, expected file owner, credit or checkout context, delivery destination, and data-rights category. That checklist keeps the exported files tied to the market and rights decision after they leave the browser flow.

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When To Reach For Exports

A Parquet export is the right call when the work is a durable dataset: offline research, a warehouse load, model training, backtesting, procurement review, or repeated access to the same historical window. The export exists because the file is the operational artifact. For agents, require a two-step plan: choose the export schema and date range first, then use the product flow or dashboard state for checkout, never an invented REST checkout route.

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Next Step

Start with Data catalog, then use Export schemas and Export checkout before loading files into a warehouse or backtest harness. Compare plans.
Last modified on August 13, 2026