> ## Documentation Index
> Fetch the complete documentation index at: https://docs.0xarchive.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Rights And Redistribution

> Use 0xArchive market data safely inside products, research systems, backtests, dashboards, and organization-owned workflows.

0xArchive sells API access to market data infrastructure. Build products, research workflows, alerts, backtests, dashboards, agent workflows, and organization-owned systems against the routes described in this portal. API access does not by itself grant the right to resell, republish, sublicense, or redistribute raw datasets outside your organization.

Data rights decide what your system can do with market data after an endpoint, export, SDK, CLI job, MCP tool, or Skill returns it. Treat raw-data redistribution as a commercial/legal boundary, not a code-generation detail.

## Practical Rule

The safe default is simple: call the API for your own application, store the records your application needs, and use the output to power analysis, models, monitoring, private dashboards, and user-facing product behavior. If your product exposes raw downloadable market data, a bulk resale path, a public archive, or a third-party feed built from 0xArchive records, review the commercial terms before shipping.

| Use case                   | Default fit       | What to check                                                            |
| -------------------------- | ----------------- | ------------------------------------------------------------------------ |
| Internal research notebook | Good fit          | API key handling, route family, freshness, reproducible request metadata |
| Backtesting pipeline       | Good fit          | Historical window, point-in-time assumptions, gap handling, request IDs  |
| Internal dashboard         | Good fit          | Caching, refresh cadence, plan limits, incident handling                 |
| Customer-facing app view   | Good fit          | Derived display, latency expectations, plan capacity                     |
| Public raw-data download   | Commercial review | Redistribution terms, volume, attribution, retention, export workflow    |
| Resold market-data feed    | Commercial review | Contract, downstream recipients, SLA, delivery model                     |

## Keep Source Context Attached To Data

Every stored dataset should carry enough context to show where it came from. Save the route, symbol, venue family, time window, query parameters, cursor chain, `meta.request_id`, freshness or quality state, and generation time alongside the payload. For Data Catalog exports, also store the job ID, schema keys, quote context, credits applied, and file format. That metadata makes a file useful to another engineer later and gives support enough context to diagnose an issue.

For example, a historical trades pull should store more than the rows:

```json theme={"theme":"github-dark"}
{
  "source": "0xArchive",
  "route": "/v1/hyperliquid/trades/BTC",
  "venue_family": "hyperliquid_core",
  "symbol": "BTC",
  "window": {
    "start": "2026-01-01T00:00:00Z",
    "end": "2026-01-01T01:00:00Z"
  },
  "request_ids": ["8f2e7f6f-7c5f-4f8d-9f14-9a6c5b4d1d8b"],
  "freshness_state": "fresh",
  "quality_status": "ok",
  "generated_at": "2026-05-08T00:00:00Z"
}
```

## Derived Products

Derived product behavior is different from raw redistribution. A trading dashboard that displays a chart, a model that consumes order-book snapshots, or an alerting system that emits “freshness degraded for BTC” is using 0xArchive as infrastructure. Keep the user experience tied to the job: show market state, risk, research output, or operational health rather than exposing a raw copy of the archive.

When a derived product still gives users bulk access to original records, treat it as a redistribution question. Common triggers are CSV or Parquet download buttons, API endpoints that mirror 0xArchive rows, scheduled exports to customer storage, and “bring your own downstream users” partner workflows.

## Data Catalog Exports

The Data Catalog is the file-first path for teams that need market history as files instead of a long-running API job. It is useful for one-off historical analysis, offline notebooks, model training inputs, and shareable delivery files. Use the quote and checkout flow when the job is a file purchase. Use the API when the job needs repeatable programmatic access.

Exports still need the same discipline as API pulls: store the market family, symbol, schema keys, date range, quote context, credits applied, delivery format, generation time, and any quality notes that affect downstream use. Credits reduce checkout cost; they do not change redistribution rights.

## Automation Guidance

Coding agents, CLI jobs, notebooks, and MCP clients can write safe pull scripts, add request-ID logging, check freshness, and save reproducible metadata. Keep redistribution decisions outside generated code. A script should not turn a private backtest into a public raw-data product or invent permission language.

<Prompt>
  Use 0xArchive to pull a bounded Hyperliquid BTC trades window. Save the route, time window, cursor chain, request IDs, freshness result, and generation time beside the rows. Do not expose the output as a public raw-data download.
</Prompt>

## Next Steps

Start with [Historical Market Data](/guides/historical-market-data) for bounded pulls, [Point-In-Time Backtesting](/guides/point-in-time-backtesting) for reproducible strategy research, and [Rate Limits And Credits](/rate-limits) for plan capacity. Use [Contact](https://www.0xarchive.io/contact) when the product needs raw redistribution, custom delivery, enterprise retention, or contract-specific rights.