It is possible to construct MBP-10 yourself from MBO data if you want more price levels or prefer to reduce your bandwidth use. Learn how to construct a limit order book from MBO data from our limit order book construction tutorial.
Examples and tutorials
Options
Equity options: Introduction
Options on futures: Introduction
All options with a given underlying
Join options with underlying prices
US equity options volume by venue
Resample US equity options NBBO
Estimate implied volatility
Get symbols for 0DTE options
Calculate daily statistics for equity options
Historical data
Request a large number of symbols
Programmatic batch downloads
Best bid, best offer, and midprice
Custom OHLCV bars from trades
Join schemas on instrument ID
Plot a candlestick chart
Calculate VWAP and RSI
End-of-day pricing and portfolio valuation
Benchmark portfolio performance
Market halts, volatility interrupts, and price bands
Resample OHLCV from 1-minute to 5-minute
Algorithmic trading
A high-frequency liquidity-taking strategy
Build prediction models with machine learning
Execution slippage and markouts
Matching engine latencies
Using messaging rates as a proxy for implied volatility
Mean reversion and portfolio optimization
Pairs trading based on cointegration
Build a real-time stock screener
Core concepts
Venues and datasets
CME Globex MDP 3.0
Cboe BYX Depth
Cboe BYZ Depth
Cboe EDGA Depth
Cboe EDGX Depth
Databento US Equities Basic
Databento US Equities Mini
Databento US Equities Summary
Eurex Exchange
European Energy Exchange
ICE Endex iMpact
ICE Europe Commodities iMpact
ICE Europe Financials iMpact
ICE Futures US iMpact
IEX TOPS
MEMX Memoir
MIAX Depth of Market
Nasdaq Basic with NLS Plus
Nasdaq TotalView-ITCH
NYSE American Integrated
NYSE Arca Integrated
NYSE Texas Integrated
NYSE National Trades and BBO
NYSE Integrated
OPRA Pillar
Corporate actions
Adjustment factors
Security master
API Reference
Resources
Release notes
C++
0.42.0 - 2025-08-19
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0.40.0 - 2025-07-29
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Python
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0.24.1 - 2023-12-15
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0.6.0 - 2022-12-02
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0.4.0 - 2022-09-14
0.3.0 - 2022-08-30
HTTP API
0.35.0 - TBD
0.34.1 - 2025-06-17
0.34.0 - 2025-06-09
0.33.0 - 2024-12-10
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0.4.0 - 2022-12-02
0.3.0 - 2022-08-30
0.2.0 - 2021-12-10
0.1.0 - 2021-08-30
Raw API
0.6.4 - TBD
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0.7.0 - 2024-03-01
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0.4.1 - 2023-10-06
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0.3.0 - 2023-09-13
0.2.1 - 2023-08-25
0.2.0 - 2023-08-10
0.1.0 - 2023-08-02
Data
2025-09-23
2025-08-26
2025-08-05
2025-07-25
2025-07-06
2025-07-01
2025-06-27
2025-06-17
2025-06-10
2025-05-20
2025-05-07
2025-04-05
2025-04-01
2025-03-13
2025-02-26
2025-02-01
2025-01-15
2024-12-14
2024-12-03
2024-12-02
2024-10-22
2024-10-24
2024-07-05
2024-06-25
2024-06-18
2024-05-07
2024-01-18
2023-11-17
2023-10-04
2023-08-29
2023-07-23
2023-05-01
2023-04-28
2023-03-07
Collapse all
Schemas and data formats
Market by price (MBP-10)
MBP-10 (market by price) 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.
This is often called "L2 data".
Fields (mbp-10
)
Field | Type | Description |
---|---|---|
ts_recv |
uint64_t | The capture-server-received timestamp expressed as the number of nanoseconds since the UNIX epoch. See ts_recv. |
ts_event |
uint64_t | The matching-engine-received timestamp expressed as the number of nanoseconds since the UNIX epoch. See ts_event. |
rtype |
uint8_t | A sentinel value indicating the record type. Always 10 in the MBP-10 schema. See Rtype. |
publisher_id |
uint16_t | The publisher ID assigned by Databento, which denotes the dataset and venue. See Publishers. |
instrument_id |
uint32_t | The numeric instrument ID. See Instrument identifiers. |
action |
char | The event action. Can be Add, Cancel, Modify, cleaR book, or Trade. See Action. |
side |
char | The side that initiates the event. Can be Ask for a sell order (or sell aggressor in a trade), Bid for a buy order (or buy aggressor in a trade), or None where no side is specified. See Side. |
depth |
uint8_t | The book level where the update event occurred. |
price |
int64_t | The order price where every 1 unit corresponds to 1e-9, i.e. 1/1,000,000,000 or 0.000000001. See Prices. |
size |
uint32_t | The order quantity. |
flags |
uint8_t | A bit field indicating event end, message characteristics, and data quality. See Flags. |
ts_in_delta |
int32_t | The matching-engine-sending timestamp expressed as the number of nanoseconds before ts_recv . See ts_in_delta. |
sequence |
uint32_t | The message sequence number assigned at the venue. |
bid_px_N |
int64_t | The bid price at level N (top level if N = 00) where every 1 unit corresponds to 1e-9, i.e. 1/1,000,000,000 or 0.000000001. See Prices. |
ask_px_N |
int64_t | The ask price at level N (top level if N = 00) where every 1 unit corresponds to 1e-9, i.e. 1/1,000,000,000 or 0.000000001. See Prices. |
bid_sz_N |
uint32_t | The bid size at level N (top level if N = 00). |
ask_sz_N |
uint32_t | The ask size at level N (top level if N = 00). |
bid_ct_N |
uint32_t | The bid order count at level N (top level if N = 00). |
ask_ct_N |
uint32_t | The ask order count at level N (top level if N = 00). |
Implementation differences between clients and encodings
Bid and ask depth messages (fields starting with bid_
and ask_
) are structured differently in the C++ and Rust clients, the Python record interface, and JSON data. Instead of using the _N
suffix, they're stored in an array of structures named levels, with the top-of-book at index 0
.
For example, in C++, levels[5].bid_px
corresponds to bid_px_05
in the Python DataFrame API and CSV format.
See also