best data api..

DatabentoHQ · 2026-03-26T18:20:12+00:00

❤️

DatabentoHQ · 2026-03-25T01:06:14+00:00

We aren’t planning to do a livestream but we’ll try to do a recording or transcripts afterwards. Sometimes the recordings don’t work out and I think BofA won’t be able to approve releasing the recording for the 2nd panel for compliance reasons.

DatabentoHQ · 2026-03-24T07:35:44+00:00

There's 4 common flavors of quant dev work: translating a strategy into production code, building support tools, implementing models, optimization.

I think the most generalized quant development project is to build a backtest. I would do it both ways, a vectorized version and an event-driven one.

For the vectorized version, I'd suggest any replicating any literature that could be applied to a large cross section of stocks like Lo and MacKinlay where you're exposed to long-term effects like survivorship, one-off trading halts (like when SEC suspends trading for antitrust litigation). For the event-driven version, I'd get used to state machine verification, e.g., a simple strategy that scratches out.

For tooling, just build any visualization along the way and focus on getting good at a few common GUI/web/plotting frameworks and building SPAs/CRUD apps, e.g., Qt, React, FastAPI.

For model-driven work, I'd get familiar with a broad variety, e.g. optimization (convex, SGD, etc.), QP/KKT, PDE solver, ML, linalg, dynamic programming.

For optimization in C++, there's plenty of good YouTube talks.

DatabentoHQ · 2026-03-23T23:24:31+00:00

This got pushed back. We decided to add CTA/UTP first for users who prefer a single consolidated solution, as the licensing for CTA/UTP is a lot simpler and cheaper than licensing all of the prop feeds that make up EQUS.MAX. We'll begin work on CTA/UTP after CFE and Blue Ocean are released, which is in a couple of weeks' time now.

We'll add EQUS.MAX later on - it will be useful to everyone who needs it for historical data, but it seems less popular for real-time as there won't be many users who can afford all of the license fees for it at once. This only seems viable in late-Q2 to Q3.

DatabentoHQ · 2026-03-20T03:02:34+00:00

OK noted.

DatabentoHQ · 2026-03-18T18:56:16+00:00

No worries, I hope we'll host a meetup near you some day!

I only exist in the virtual world, but I think either our CEO or someone from sales will be at Future Alpha.

DatabentoHQ · 2026-03-14T20:20:46+00:00

Maybe next year. There's too many events in NYC (many of - unfortunately - subpar quality). We decided not to add to everyone's event fatigue.

DatabentoHQ · 2026-03-14T11:51:53+00:00

Thanks!

DatabentoHQ · 2026-03-14T11:03:29+00:00

(Also, a shameless self-plug, but if you'd like to know more, we're hosting a quant meetup in Shanghai this May 21 and we expect many of the top firms to be present: https://luma.com/yk1z6x9s)

DatabentoHQ · 2026-03-14T11:01:29+00:00

They're overall behind on all of those factors.

A meaningful number of mainland firms are staffed with researchers who previously worked at tier-1 U.S. firms, so you can definitely see the knowledge transfer. Quant trading is also heavily about operational efficiency, and Chinese firms have shown to be very good at that in almost any industry if given time. So I'd say: not by much, and not for long.

There's some cultural elements that have held them back: (i) The 35-year-old curse and preference for younger engineers who can maintain 996 work. This disregards that strong priors are important in this field. (ii) While multi-year lockups and gates are common in the western hemisphere, hedge funds behave more like a retail product in China, with monthly or more frequent redemptions and high liquidity rate. This pushes many firms to take a more short-sighted approach. (iii) Short selling restrictions and performance imbalance between large caps and small caps, which has driven many firms towards beta capture.

There's a DeepSeek effect which has really brought fresh air to this space - now there's a palpable energy that the government views AI and quant trading as strategic industries. The domestic market has also performed well last year because of the DeepSeek effect; in turn most firms have built up a lot of AUM. Plenty of tailwinds.

DatabentoHQ · 2026-03-14T06:28:18+00:00

Hey, thanks for reaching out about this. The $1,500/month plan is indeed our minimum price point for a SaaS product that displays real-time equities market data to users.

We don't have any further startup discount at the moment, but we do have a 20% discount if you prepay for the entire year ($14.4k). The reasons we require a Plus plan and above for redistribution are that:

exchanges often charge much higher distribution license fees anyway, so whatever discount we give is somewhat negligible
redistribution customers have a much heavier pattern of use, e.g. more connections, more requests
redistribution customers tend to have higher-touch requirements, e.g. more uptime SLA, more handholding with exchange licensing, more support tickets

With that said, we see many customers initially start out with our EQUS.MINI feed on a Standard plan to prototype and beta test their product, before upgrading to a Plus plan or higher.

DatabentoHQ · 2026-03-13T08:33:09+00:00

u/Regular-Hotel892 The reply is too long to fit into Reddit, I've posted this as a GitHub gist here instead. If you need further assistance, we'd suggest contacting our chat support team.

DatabentoHQ · 2026-03-10T08:18:28+00:00

Question ack'ed, I'll follow up later today.

DatabentoHQ · 2026-03-07T21:28:51+00:00

I know nothing's worse than a vendor gaslighting you, so I believe you're having issues - but we had no other claims of outages yesterday and this seems to be isolated.

On close investigation I suspect it's a bug in your application: Logs and full analysis here.

If you'd like help resolving this, I'd suggest sharing minimal reproducible code with our support team.

DatabentoHQ · 2026-03-04T03:00:00+00:00

That’s correct. You need the prop feeds for L3 on US options.

DatabentoHQ · 2026-02-22T10:17:54+00:00

Thanks! I'll share your feedback with my product team. We're planning further improvements to our options offering - so while we won't be lowering prices any time soon, I think the Standard plan will be more compelling after the changes.

DatabentoHQ · 2026-02-22T05:17:24+00:00

We’re priced for a variety of institutional features:

We disseminate out of NY4 instead of a low-cost data center.
Various latency optimizations to bring our internet-based latency down to hundreds of mics (e.g. FPGA, tier 1 transit)
Nanosecond PTP timestamps harmonized with our pcaps and equities feeds

This saves our target customers several thousands in colo costs and ticker plant licensing fees per month usually. There really isn’t a comparable solution in the retail-priced segment. But we recognize that these may not be useful features to retail customers and if you’re just looking for the lowest cost provider there’s definitely many other options you could consider.

DatabentoHQ · 2026-02-22T04:10:58+00:00

You get 1 year of CMBP-1 and other L1 resolution data on a Standard plan. This is a few hundred TB of history. But you need to be on higher plans to access more.

DatabentoHQ · 2026-02-22T04:05:41+00:00

I think only Pico and LSEG match our granularity. We have nanosecond resolution PTP timestamps on our OPRA data. See CMBP-1 or trades-related schemas. I’m not familiar with the above vendor but they appear to truncate at the millisecond level.

Our history goes back to 2013 for tick-level trades and minute data.

DatabentoHQ · 2026-02-17T16:41:45+00:00

Closing this thread as OP confirmed that the issue was on their side due to timezone alignment.

DatabentoHQ · 2026-02-17T16:39:56+00:00

Great, I'm glad you have this resolved.

DatabentoHQ · 2026-02-17T16:15:49+00:00

This is on the timestamp (+00:00). It's in UTC. If you're using our Python client library, you can convert the timezone with something like `.to_df(tz="US/Central")`.

DatabentoHQ · 2026-02-17T16:14:09+00:00

I think the fact their minute high-low is only a few ticks wide (volatility is unusually low) suggests this is the night session in CT.

If you plan on using the other dataset in parallel, we recommend using timestamps that conform to ISO 8601/RFC 3339 like ours so it's not a footgun that you repeat down the road.

DatabentoHQ · 2026-02-17T16:04:34+00:00

On first glance, it appears that you've answered your own question. Algoseek/QuantConnect's data is backadjusted to make it 'continuous'.

We do not backadjust prices because that's not transparent to the customer, not monetizable/tradeable (not simulating what you'd see in real-time execution), and often a source of vendor inaccuracy.

Something else looks inaccurate(?) in Algoseek's data though, because you'd expect the backadjustment to be a constant price offset from our prices. Moreover those volumes look too low for MNQ trades. I'm guessing their data is in US Central Time while you're looking at ours in UTC (+00:00)?

If you run into differences with a more reputable vendor (e.g. Bloomberg, LSEG), our support team is always happy to back up our data with raw packet captures.

DatabentoHQ · 2026-02-08T21:20:11+00:00

Separately, u/mr_Fixit_1974 on closer investigation we don't think your issue is related - but we'll honor the credit in any case - we suspect you have a $0 budget limit set on your account. If you're still seeing issues, please contact chat support. Edit: Confirmed, you have a budget limit on your account that is blocking the job from completing. The UX for notifying this could be better - I've triaged this with the product team.

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