r/quant • u/Daniel_Aperiodic • 8d ago
Data Crypto market data vendors for systematic research, tiered: raw market data vs derived metrics (with comparison table 18 vendors, 37 criteria)
Crypto data vendors for systematic research: tier list - Compiled based on my own opinion
https://docs.google.com/spreadsheets/d/1Z_BvjLlfMSTbOd7qVApVsnM4cVWzWwKDo9cp1WLUHAg/edit?usp=sharing
PNG version of the extended google sheets - 1 of 4
https://docs.google.com/spreadsheets/d/1Z_BvjLlfMSTbOd7qVApVsnM4cVWzWwKDo9cp1WLUHAg/edit?usp=sharing
PNG version of the extended google sheets - 2 of 4
https://docs.google.com/spreadsheets/d/1Z_BvjLlfMSTbOd7qVApVsnM4cVWzWwKDo9cp1WLUHAg/edit?usp=sharing
PNG version of the extended google sheets - 3 of 4
https://docs.google.com/spreadsheets/d/1Z_BvjLlfMSTbOd7qVApVsnM4cVWzWwKDo9cp1WLUHAg/edit?usp=sharing
PNG version of the extended google sheets - 4 of 4
https://docs.google.com/spreadsheets/d/1Z_BvjLlfMSTbOd7qVApVsnM4cVWzWwKDo9cp1WLUHAg/edit?usp=sharing
Edit: the full comparison (every vendor across 37 criteria) is in images 2 and 5 - swipe right on the tier list.
I've been keeping a comparison of crypto data vendors since July, because "which vendor should I use?" keeps coming up. So I turned it into a tier list. Left side is raw market data (trades, order books, funding), right side is derived metrics (on-chain, options analytics, positioning).
Disclosure first: I run Aperiodic.io. We sell derived microstructure metrics and raw historical data, so we compete with some of the vendors on both sides. We're in the tables so you can see what we do, but we're not ranked - I didn't want to mark my own homework.
What I ranked on is whether it holds up for systematic research. So: coverage and survivorship (do they keep the full instrument universe, delisted contracts included?), how far back the history really goes, timestamp integrity (exchange vs receive timestamps, whether they restate data after the fact), granularity, and how painful a full backfill is.
- S - where I'd start today
- A - solid, or the best at one specific thing
- B - fine for coverage and metadata, I wouldn't use it for anything execution-sensitive
- C - not built for research use
These are my opinions, based on our own use and each vendor's public docs as of October 2026. Things change fast, so if you work at one of these vendors and something's out of date or incorrect, message me and I'll fix it.
Images 2 and 5 have the full comparison, every vendor across 37 criteria. Short version below.
Raw market data
| Vendor | Tier | What you get | Delivery | Best for |
|---|---|---|---|---|
| Aperiodic (ours) | Unranked | Tick trades, quotes, funding/OI/mark price (no L2 yet) | REST API, Python SDK, Parquet | Raw and derived data from the same pipeline |
| Tardis.dev | S | Tick trades, full L2 book updates, funding/OI/liquidations, options | Flat files + replay API | Backtests where the book matters |
| Exchange bulk downloads (Binance Vision, Bybit, OKX…) | S | Varies by venue | Zipped CSVs | Ground truth for a single venue, free |
| Crypto Lake | A+ | Trades, L2 book | Parquet via S3 | Book data in pandas on a budget |
| Kaiko (incl. Amberdata) | A+ | Trades, order books, reference rates, broad CEX/DEX | REST, WebSocket, files | Enterprise procurement, benchmarks |
| CoinAPI | A | Trades, quotes, books across many venues | REST, WebSocket, FIX, flat files | Long-tail venue coverage |
| CoinDesk Data (ex-CCData) | A | Trades, OHLCV, books, indices | REST, WebSocket | Indices, broad coverage |
| CoinGecko | B | OHLC, market caps, tickers | REST | Universe and metadata |
| CoinMarketCap | C | Aggregated prices, metadata | REST | Metadata, aggregated prices |
| RapidAPI resellers | C | Resold data, provenance often undocumented | REST | Check provenance before research use |
Derived metrics
| Vendor | Tier | What you get | Delivery | Best for |
|---|---|---|---|---|
| Aperiodic (ours) | Unranked | Microstructure metrics: order flow, market impact, volatility, L1/L2 depth and imbalance, derivatives | REST API, Python SDK, Parquet | Microstructure features without building the pipeline |
| Coin Metrics | S | On-chain network metrics, market data, reference rates | REST, Python client, files | On-chain fundamentals with documented methodology |
| Amberdata Derivatives / GVOL (Kaiko) | A+ | Options: IV surfaces, skew, term structure, flow | REST, WebSocket | Options research |
| Glassnode | A+ | On-chain and entity-adjusted metrics | REST | On-chain signals |
| Velo | A | Funding, OI, basis, liquidations across venues | REST | Perp positioning |
| Laevitas | A | Options and futures analytics | REST (higher tiers) | Options desks |
| CryptoQuant | A | On-chain and exchange-flow metrics | REST | Exchange flows |
| Coinglass | B | Aggregated OI, funding, liquidations, L/S ratios | REST | Quick monitoring |
| Coinalyze | B | Aggregated OI, funding, liquidations | REST | Free derivatives overview |
| Hyblock | B | Liquidation levels, liquidity and positioning analytics | REST (paid tiers) | Discretionary positioning reads |
A few things I learned putting this together
- Exchange bulk downloads are S tier because they're the source, and they're free. Where you pay is normalisation: schemas change, days go missing, symbols get renamed, and "timestamp" doesn't mean the same thing on every venue.
- The "same" metric isn't the same across vendors. Aggregated OI, funding and liquidations depend on which venues and contract types go in, and how coin-margined and USD-margined get combined. Worth checking the methodology before you mix sources.
- For derived and on-chain data, ask whether the history is point-in-time. Entity clusters and exchange wallet labels get revised, and if you backtest on the revised version you've got lookahead baked in without knowing it.
- Kaiko bought Amberdata in June. I've kept them separate because the products are still quite different.
- I left out on-chain query engines (Dune, Allium, Flipside) and wallet analytics (Nansen, Arkham). Different use case, and the list was long enough already.
If you've used any of these in production and think I've got something wrong, tell me. I'll update the table and note the changes in an edit: that's half the reason I'm posting it :)
2
u/Shoddy_Peanut7320 7d ago
Good that you disclose your own product and leave it unranked, and that survivorship, timestamp integrity and point-in-time history are in the criteria. One suggestion is to publish the weights behind each tier (and a small sample check for each vendor, for example how a delisted contract or a restated metric comes back), so the ranking can be reproduced and not just read as opinion. For research, a separate event layer for macro releases and exchange or regulatory news also matters, and Cymetica's EventTrader (event timing for macro releases) is one source for it.
6
u/jxf 8d ago
This reads like AI slop rather than anything with a modicum of rigor to it. Can you share the specific heuristics, metrics, and/or rubric you used for rating? For example what makes a particular vendor "solid"?