Product roadmap

The current coverage for EEX covers futures and options on futures, but gas spot contracts are not currently part of the coverage. In the scope of this ticket, add support for EEX gas spot contracts under the XEEE.EOBI dataset.

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.

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.

To extend support to browser-based applications.

This serves as a master list of all other snapshot-like features on our roadmap. The scope of this ticket is potentially very large and ambiguous so we've broken this down into smaller tickets that you can follow separately. (Historical only) https://roadmap.databento.com/b/n0o5prm6/feature-ideas/add-historical-endpoint-for-latest-snapshot-of-any-schema. This would allow a user to get the latest published value of any given schema, within the boundaries allowed by licensing/entitlements/historical embargo window. The main benefit of this is for creating ticker tape or latest quote features, e.g. on a web app, after we start exposing intraday data over the historical/HTTP API (https://roadmap.databento.com/roadmap/expose-intraday-and-current-trading-session-historical-data-over-historical-http-api-and-clients). Likely endpoint names for this would be either timeseries.get_last or timeseries.get_snapshot. (Historical only) https://roadmap.databento.com/b/n0o5prm6/feature-ideas/provide-snapshots-as-of-specified-time-in-historical-api. Likely endpoint names for this would be either timeseries.get_last or timeseries.get_snapshot.(Live only) https://roadmap.databento.com/roadmap/add-periodic-mbo-book-snapshots-to-live-api. This allows a user to get the last published value of any given schema at a specified time. The main benefit of this would be to allow customers to subsample the data on server side and reduce cost, though the benefit is diminished with feature 5 on this list. Note that this would allow a user to emulate (1) relatively well since a user could potentially just pass in their current clock time or some time slightly ahead of the clock time. However, their underlying implementations would be different and (1) and (2) would likely be released separately. Likely endpoint names for this would be either timeseries.get_last_asof or `timeseries. (Live only) https://roadmap.databento.com/b/n0o5prm6/feature-ideas/allow-live-api-clients-to-request-for-mbo-snapshot-recovery. This provides resilience to gaps or data errors originating from Databento side. It could also be used for recovery of book state caused by client-side issues or disconnection, but would be less quick than feature (4) on this list.(Both historical and live) https://roadmap.databento.com/roadmap/fixed-interval-mbp-1-summaries-eg-1-minute-bbo-or-subsampled-bbo. The purpose of this is more to provide customers a convenience over fetching or subscribing MBP-1 and subsampling and forward filling the MBP-1 data themselves, which could be very expensive given the size of MBP-1 data and how the customer has no idea how far to look back for the "last" MBP-1 update prior to the 1 second or 1 minute refresh interval. Some of these are in development, hence the status of this entire ticket, however you should check on each individual one in case the specific feature you're looking for is still in Considering state.

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

Historical and live market news.

Only regular trading hours are supported currently.

At the moment, options data users have to rely on fetching the definition schema and filtering for symbols that they're interested in using fields like expiration, asset, underlying_product, instrument_class, group, and strike_price. It would be convenient to fetch the options or options chains with particular conditions on expiration and strike price without going through the definition schema. This would be similar to smart symbology for futures. Note that even after this feature is released, we still recommend users to use definition as it gives more control and transparency over the symbology resolution.

Via streamlined SBE.

National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) data.

Databento's feed is based on CME's MBO feed and we do not overlay implied depth from the MBP feed. This creates the appearance of less liquidity and wider spreads compared to many vendors that are only using the MBP feed. Overlaying MBO and MBP creates several complications; we think using the direct book is better for signal generation and execution, and prefer not overlay implied MBP over MBO to form a composite book. At this time, users who are sensitive to implied orders can impute the implied book themselves. That said, we may expose the implied book for users who find this useful and prefer to compare our data to another reference.

Adding support for the CBOE Complex Options Order Feed, which provides detailed insights into complex order activity across CBOE markets. This includes multi-leg strategy orders, spread data, and intricate order types that are vital for understanding advanced options trading strategies. Key Features: -Real-time and historical data on multi-leg orders. -Visibility into pricing and execution of complex options strategies. -Detailed breakdowns of spread and combination order flows.

Exchange fees, e.g. clearing, rebates, etc. (e.g. for CME Group and Eurex) Also in parallel, a similar dataset that's useful would be historical borrow costs.

https://www.nodalexchange.com/resources/market-data/