Product roadmap
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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 Hollinger19
Parquet encoding
Support Parquet as a form of encoding, aside from dbn, CSV and JSON.
Tessa Hollinger12
Index component weightings
e.g. for S&P 500.
Tessa Hollinger5
London Metal Exchange (LME)
Futures and options on futures from LME. This will be captured at LON2 colo and include both L2 (for implied pricing) and L3 feed (order-by-order). Lower granularities like OHLC, OI, settlement volume, etc. will be included as well
Felix E1
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
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
Official Java client library
Make our historical and live APIs easier to integrate from Java.
Carter Green6
Nasdaq Nordic data
Data for: Copenhagen Stock Exchange (Nasdaq Copenhagen) Stockholm Stock Exchange (Nasdaq Stockholm) Helsinki Stock Exchange (Nasdaq Helsinki) Iceland Stock Exchange (Nasdaq Iceland) Tallinn Stock Exchange (Nasdaq Baltic) Riga Stock Exchange (Nasdaq Baltic) Vilnius Stock Exchange (Nasdaq Baltic)
Tessa Hollinger6
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 Hollinger33
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)8
Support for Global Trading Hours (GTH) on OPRA US options data
Only regular trading hours are supported currently.
Carter Green8
Machine-readable news feed (live and historical)
Historical and live market news.
Renan Gemignani (Databento)1
JPX Futures
It would be great if Japan Exchange Group (Nikkei 225, etc) could be supported. CME Nikkei 225 volume is too low.
Michael Aaron B9
US equity trade condition codes
Add trade reporting modifier flags, e.g. those found in CTS sale conditions here: https://www.nyse.com/publicdocs/ctaplan/notifications/trader-update/cts_output_spec.pdf Similar to: https://roadmap.databento.com/b/n0o5prm6/feature-ideas/include-opra-trade-conditions
Luca L5
Singapore Exchange (SGX) data
Stocks and derivatives data from the Singapore Exchange (SGX)
Carter Green1