Product roadmap
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Binance data (cryptocurrency spot, futures, options)
We've received some requests recently for Binance data. Please upvote if this is of interest. We're still determining whether this is worth the risk.
Christina Qi2
Trading calendar information
This feature would allow the user to request trading calendar information (such as trading session start/end times) via our API. This is especially useful when considering trading sessions that can span multiple UTC dates (and hence the possibility of having multiple trading sessions within a single day). Keywords: Market calendar, trading holidays.
Renan Gemignani6
London Metal Exchange
futures and futures options OHLC, OI and volume from the LME
Felix E0
Support subscribing to all futures only or all options only on CME MDP 3.0
Currently there's no possible way to subscribe to all CME futures in a bundle or all CME options in a bundle, only the combination of both.
Tessa Hollinger0
WebSocket API for live data
To extend support to browser-based applications.
Tessa Hollinger6
Parquet encoding
Support Parquet as a form of encoding, aside from dbn, CSV and JSON.
Tessa Hollinger11
Official C# client library
This client library makes all our historical and live features easier to integrate in C# on Windows, Linux, and Mac OS. C# is currently already supported through our HTTP API and Raw TCP protocol, which are both language-agnostic.
Tessa Hollinger12
CME trading session hours
It might be possible to obtain CME trading session hours systematically in historical captures of the instrument definition messages, as embedded in tag-1682=MDSecurityTradingStatus. This ties to another proposed feature here.
Tessa Hollinger1
Expose metadata of every underlying leg in multi-leg futures and options
Currently, multi-leg products (spreads, strategies, combos) on CME/ICE are hard to use because our instrument definitions do not provide metadata about each underlying leg. The user has to infer the legs from the symbol. This is a form of lossy normalization, since CME/ICE does provide this in their security definitions in a repeating group, but our fixed instrument definition schemas are forced to discard thisβthey only provide the the instrument_id of the first underlying instrument through underlying_id. In the meantime, our recommendation to users is to either infer this from the symbol OR download the raw security/instrument definitions from the exchange (e.g. CME's is free on their FTP) OR get a pcap subscription from us. If you need historical secdefs copied from CME (since their FTP site only gives 1 day history), we can provide a courtesy backfill of these for a fixed cost.
Tessa Hollinger10
Example Liquidity Heatmap on MBO Data in Python
Documentation for how to use the the order book from MBO data for visualizing the evolution of limit order book over time as heatmap. For instance every 10 seconds a snapshoot of the order book of historical 6E futures data is taken. Now a heatmap (exp.: Seaborn) is generated, showing price levels on y axis and timeincrements of 10 seconds on the x axis. The color intensity of the boxes depends on the size of the limitorders. Maybe this idea is an good example for implementing the heatmap with json, d3, ...
Daniel B3
Include OPRA trade conditions
It would be helpful if OPRA trade conditions were included in the normalized schemas. This is useful information that's currently lost during normalization. Also include the "message type" of each last sale message. Similar to: https://roadmap.databento.com/roadmap/us-equity-trade-condition-codes
Carter Green2
AWS S3 delivery
Support AWS S3 as an additional method of delivery, aside from HTTP and FTP.
Tessa Hollinger1
Add Polars support to `to_df` method
Could we add support to make the result of DBNStore.to_df a Polars dataframe as well? Perhaps the function signature could just be overloaded with a to_polars: bool argument. Something like: In Python @overload def to_df(self, to_polars: Literal[False]) -> pd.DataFrame: ... @overload def to_df(self, to_polars: Literal[True]) -> pl.DataFrame: ... Or, maybe to_df is split into two different functions to_pandas and to_polars. Either way, it would be helpful to avoid having to do pl.from_pandas(store.to_df().reset_index(drop=False)). Plus, Polars can convert to pyarrow-Pandas zero-copy, but not the other way around.
Aidan L2
Add dark mode
Original request from Juan Linares: "Great product but please add dark mode." There are two separate parts to this: Dark mode for the portal and main website (databento.com, databento.com/portal) Dark mode for the docs We can consider this only after Q1 2025 since we're doing a major rebranding of our website which is expected to finish by early April 2025. The new colors will make it easier for us to implement a dark mode.
Juan L1
Real-time and historical index data
Currently, indices are indirectly supported through tradable index instruments on CME futures, ETFs, etc. and we don't provide the index values (non-tradable) themselves. This may be sourced from a feed like the Cboe Global Indices Feed or NYSE Global Index Feed.
Tessa Hollinger25