Product roadmap

Submit dataset requests and feature ideas here. For bug reports, use our chat support or issues tracker instead.

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  1. London Metal Exchange

    futures and futures options OHLC, OI and volume from the LME

    Felix E

    0

  2. Equities reference, fundamental and static data

    e.g. Shares outstanding, short interest, market capitalization, P/E ratio etc.

    Tessa Hollinger

    3

  3. Official Java client library

    Make our historical and live APIs easier to integrate from Java.

    Carter Green

    5

  4. 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 thisβ€”they 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 Hollinger

    13

  5. Support for Global Trading Hours (GTH) on OPRA US options data

    Only regular trading hours are supported currently.

    Carter Green

    6

  6. 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 L

    2

  7. B3 UMDF Dataset

    B3: Brazil Equities and Futures MBO data. Keywords for search purposes: Brasil Bolsa BalcΓ£o S.A., Brazilian Mercantile and Futures Exchange (BM&F), BMF, Bovespa (SΓ£o Paulo Stock Exchange), Cetip (Central of Custody and Financial Settlement of Securities for the organized OTC market).

    Renan Gemignani (Databento)

    4

  8. 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 L

    2

  9. Canadian exchange (TSX) data

    Equity data from TSX with broker IDs (TSX is one of the few markets out there with post-trade transparency)

    Marius Z

    1

  10. Kalshi data

    Kalshi is a regulated exchange where you can trade on the outcome of real world events: https://kalshi.com/

    Tessa Hollinger

    0

  11. Open close data

    Open-Close data delivers comprehensive volume analytics for options trading across all Cboe exchanges (BZX, C1, C2, EDGX), offering granular insights into market participant behavior to help you respond quickly and precisely to market changes and make better-informed trading decisions.

    GMFeed

    0

  12. 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 Hollinger

    30

  13. 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 Gemignani (Databento)

    6

  14. CFE Book Depth

    Full depth of book feed for Cboe Futures Exchange (CFE). CFE contains volatility futures and corporate bond index futures, such as VIX futures (VX, VXM).

    Zach Banks

    13

  15. Consolidated US equities data

    Currently, equities is supported via individual prop feeds of each venue. While NASDAQ is sufficient for getting NBBO for most of the time, some users prefer something that will be more in line with actual NBBO from SIPs. This feature request tracks 3 possible modes of consolidation for both historical and live data: Databento server-side consolidation of multiple proprietary feeds Consolidated data from proprietary feed like Nasdaq Basic in lieu of SIP Consolidated data from CTA/UTP SIPs We plan on implementing 1-2 of these three options.

    Tessa Hollinger

    14