What's a schema?

Databento supports over 15 different data formats of market data. When you make a request from Databento, you must usually specify which data format—also called a schema—to receive your data in.

Supported schemas and their fields

A schema represents a collection of data fields. The following is a summary of schemas supported by Databento. Click on any schema below for its details, the fields included, and a data dictionary that defines each field.

Market by order (MBO) provides every order book event across every price level, keyed by its order ID. This allows you to determine the queue position of each order and provides the highest level of granularity available.

Market by price (MBP-10) provides every order book event across the top ten price levels, keyed by price. This includes every trade and changes to aggregate market depth, alongside total size and order count at the top ten price levels.

Market by price (MBP-1) provides every order book event that updates the top price level, also known as the best bid and offer (BBO). This includes every trade and changes to book depth, alongside total size and order count at the BBO.

Consolidated market by price (CMBP-1) provides every order book event that updates the top price level across all venues in the dataset, also known as the consolidated best bid and offer (CBBO). This includes every trade and changes to book depth, alongside total size and publisher attribution at the CBBO.

BBO on trade (TBBO) provides every trade event alongside the BBO immediately before the effect of each trade. This is a subset of MBP-1.

Consolidated BBO on trade (TCBBO) provides every trade event alongside the consolidated BBO immediately before the effect of each trade. This is a subset of CMBP-1.

BBO on interval (BBO) provides the last best bid, best offer, and sale at 1-second or 1-minute intervals. This is a subset of MBP-1.

Consolidated BBO on interval (CBBO) provides the consolidated last best bid, best offer, and sale at 1-second or 1-minute intervals. This is a subset of CMBP-1.

Trades provides every trade event. This is a subset of MBO.

Aggregate bars (OHLCV) provide open, high, low, and close prices and total volume aggregated from trades at 1-second, 1-minute, 1-hour, or 1-day intervals.

Instrument definitions provide reference information about each instrument, which includes properties like symbol, instrument name, expiration date, listing date, tick size, and strike price.

Imbalance provides auction imbalance data such as paired quantity, total quantity, and auction status.

Statistics provides official summary statistics of each instrument that's published by the venue. This generally includes properties like daily volume, open interest, preliminary and final settlement prices, and official open, high, and low prices.

Status provides updates about the trading session, such as halts, pauses, short-selling restrictions, auction start, and other matching engine statuses. The granularity and frequency of these updates vary by publisher and dataset.

See also

The MBP-1, BBO and TBBO schemas, as well as the CMBP-1, CBBO, and TCBBO schemas, all provide top of book data with different update space and sampling intervals. Learn more about their differences in our MBP-1 vs. BBO vs. TBBO schemas guide.

Why are Databento's naming conventions different from third parties?

Databento avoids terms like Level 1 (L1) or Level 2 (L2) due to their inconsistent application. For example, some vendors refer to both MBO and MBP data as L2, while others strictly refer to MBP data as L2. More misleadingly, many vendors refer to MBO data as L3, even though this doesn't follow any major trading venue's naming convention.

Likewise, the term tick originates from the concept of a ticker tape and only refers to trades, not resting limit orders. This becomes a source of confusion when vendors use the term tick data to refer to either MBO or MBP data when it should be strictly reserved for trades data.

See also

For more Databento naming conventions and key terminology, visit our FAQs.

Special cases

Our MBO, MBP-1 and MBP-10 schemas adopt the following conventions in these special cases:

• Combining MBO with trades feed: Typically, MBO data provides the highest granularity, but certain venues enhance their trades feed with additional information like trades not reflected in the MBO feed, consolidated NBBO, and more. In these cases, we document the exception in our Venues and datasets section and recommend that you request both our MBO and trades schemas if you need the highest level of granularity.

Deriving one schema from another

Databento captures market data directly from the source and is only subscribed to the most granular feed(s) available from each publisher. Order book feeds are usually normalized into our MBO schema and top-of-book feeds are usually normalized into our MBP-1 schema.

To ensure consistency between schemas, Databento doesn't source the less granular schemas from separate feeds. Instead, Databento derives all of the less granular schemas starting from the most granular schema available. As you may have noticed from our schema's descriptions, the majority of them—MBP, BBO, TBBO, trades, and OHLCV—are simply derived from MBO data.

Likewise, you can also derive one schema from another losslessly on the client side, and you should expect your self-derived data to be consistent with ours. For example:

• MBP-1, BBO, and Trades can be derived from MBP-10.
• BBO, TBBO, and Trades can be derived from MBP-1.
• Trades and OHLCV can be derived from TBBO.
• OHLCV can be derived from Trades.

Deriving your own schema is useful for various reasons:

• The data needs to be defined differently for your application.
• Our derivation differs from those of another vendor and you want transparency.
• You can cut down the number of API requests made to Databento by getting the most granular schema that you need and deriving the rest yourself.
• Databento provides MBP-10 merely as a convenience feature. You can reduce bandwidth requirements, latency, and transfer time significantly by deriving MBP-10 yourself from MBO.

This is especially relevant for OHLCV, which can vary depending on how trade breaks or market halts are managed, how the start and end of each time interval are determined, and how illiquid instruments are handled if there are no trades over a given time interval. If these considerations are trivial for your use case, Databento offers OHLCV data in multiple time intervals (seconds, minutes, hours, and daily) for your convenience.

The table below summarizes which schemas can be derived from the another. Each row represents the original schema, and each column represents schemas that you can derive from the original schema.

See also

Learn how to resample trades data to other intervals, such as 5-minute intervals, from our bar aggregation tutorial.

You can also learn how to generate MBP-10 from MBO data using an order book, as seen in our limit order book construction tutorial.