FAQ

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We have a dedicated page for exchanges status.

Please follow this link: Supported exchanges

We have a dedicated page for available datasets.

Please follow this link: Supported datasets

We have a dedicated page for supported output formats.

Please follow this link: Supported formats

Order book updates (aka L2 orderbook data) is the most granular type of orderbook data that most exchanges provide.

It contains updates of the book keyed by price levels. Each time a price level in the book changes (i.e. has its quantity updated, or is deleted), an update is recorded.

Orderbook snapshots is a limited snapshot of the book. As opposed to updates, a snapshot contain all book levels from the best bid best offer (BBBO) up to N level higher.

An snapshot is output either:

• At Each time a book level is updated (very verbose).
• At a specific frequency: each new update in the orderbook happenening between two snapshots will be batched in the next snapshot.

At order time, you can select if you want snapshots to happen at each update or every N seconds, and also the number of levels you need. This has a big impact on the volume of data that will be produced, as frequent snapshots with a lot of levels will produce very big files.

Orderbook updates are the most granular orderbook data available, but it requires processing in order to be useful in a backtesting process.

The advantage of using updates is that is they are more compact in terms of space compared to snapshots.

The drawback is that your backtesting process must comprise a reconstruction step most of the times in order to do something useful with this data.

Snapshots are reconstructed from updates in our data process. You can always reproduce book snapshots from updates by replaying each update on top of the partial orderbook provided at the beginning of an updates session.

However, if your backtesting process involves querying the orderbook at each time, you might prefer using already reconstructed snapshots to save you the hassle of doing it yourself, and avoid potential issues or bug in this process.

Any company or individual who wants to explore in depth what happens on crypto exchanges can make use of this data. Proprietary trading firms, indie quants, research institutions, etc. are welcome to use our data!