Product roadmap

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.

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)

Currently, n and v continuous symbology is supported in historical data but not live data. Live data only supports c (calendar-based) continuous symbology, which is less useful.

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).

This ticket tracks the feature of releasing historical data as early as permissible. Currently, we embargo historical data strictly at a 24h cutoff to ensure that it is distributed safely as historical data for every venue, thus sidestepping real-time/delayed licensing requirements for our users. However, many venues actually define their "historical" boundary as the same date in venue local timezone OR the session end. So in theory, if a session ends at 8 PM ET, it would be possible to distribute data from the same day at 7.59 PM ET at 8 PM ET. Currently, to get data from within the trading session, you must use the live API (through Raw API or a live client of the Raw API). However, the Raw API can be unwieldy for a range of use cases that require a small amount of data from the current trading session. For example, if the user only needs a few instrument definitions, settlement prices, or wants to update a ticker tape based on subsampled OHLCVs, it is usually preferred to use a request-response model like our HTTP API; setting up and tearing down a stateful TCP subscription for the live API is probably too hefty for this feature. Once released, users should be able to access intraday historical data via HTTP API so long as they have a live data entitlement. See also: https://roadmap.databento.com/b/n0o5prm6/feature-ideas/provide-snapshots-for-historical-and-live-data

Add a schema for calculated metrics like options greeks, e.g. implied volatility, delta, etc.

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 this—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.

Right now you can go from DBN to Pandas dataframe but not the other way around. I want to merge 2 datasets and save it as a DBN file.

Futures Symbol : NQ The fields: DateTime, Open, Close, High, Low, Volume, AskVolume, BidVolume. interval: 1 minute duration: One year history data The most important is that the data must include the acurate AskVolume and BidVolume Traded. How much does it cost? Thank you very much for your help.

Hello, you have just replied to me in a previous chat that you have the availability of an SPX options history per second. You proposed OHLCV-1s so I guess they are ‘last trade’ date and not ask/bid. I am more interested in the BBO on interval (BBO) type in case it is available. How many years of history do you have for SPX options BBO on interval (BBO)? Can I request a quote for such data? Thank you Translated with DeepL.com (free version)

To extend support to browser-based applications.

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.

Data for Eurex, including all schemas (MBO, MBP, ohlcv, etc.).

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.

For options, including in the CME and OPRA datasets, the existing MBP-1 schema can have significant record volume despite the instruments being extremely illiquid. In practice, there are several orders of magnitude more MBP-1 records than trades, which is unwieldy to work with. We're introducing a new schema to resolve this. BBO on interval (bbo-1s, bbo-1m) will provide the last best bid, best offer, and sale at 1-second or 1-minute intervals. This is different from BBO on trade (tbbo), which is a subset of our MBP-1 schema and provides every trade event alongside the BBO immediately before the effect of each trade. The main distinction is that TBBO is captured in trade space, while BBO is captured in time space. Learn more in our MBP-1 vs. TBBO vs. BBO schemas guide. Update: The BBO schema will be supported for all symbols on all datasets, not only options. This description focuses on options as that's where the benefit would be maximized (since options have much larger order-to-trade ratios). We'll roll this out for CME first, followed by equities and ICE, and then OPRA.