You have a solid alpha signal. You've backtested it on 10 years of cleaned OHLCV data and the Sharpe ratio holds up across bull and bear markets. You spin up a paper trading system, connect it to a broker, and wait.
The fills start coming in — and the slippage destroys you.
Your strategy worked on 1-hour candles. The actual execution lives at the tick level. The bid-ask spread, the queue position, the microprice shifts — these are the forces that your backtest never captured because you never had the data to capture them.
This is the moment many quant developers hit a wall. They go looking for US equity tick data, compare vendors, and land on Polygon.io as the clear leader. Then they notice something: TickDB doesn't offer US stock tick data. And they wonder — why not? Is this a gap? An oversight? A strategic failure?
It's none of those. This article explains exactly what TickDB does and doesn't offer for US equities, why those boundaries exist, and how to architect your data stack when you need capabilities that live outside TickDB's scope.
The Question Behind the Question
Before diving into the technical details, it's worth naming what users are actually asking when they ask why TickDB doesn't support US tick data.
The underlying question is almost never "does this product have feature X?" The question is: "can I build my system with this product alone?"
The answer for US equity tick data is no — and that's intentional.
TickDB's scope covers:
- Historical OHLCV (kline) for US equities: 10+ years of cleaned, aligned daily and intraday candles suitable for cross-cycle strategy development and backtesting
- Depth channel (order book) for US equities: Level 1 best bid/offer data via WebSocket subscription
- Real-time and historical kline via REST and WebSocket
- Cross-asset coverage across forex, crypto, Hong Kong stocks, A-shares, commodities, and indices
What TickDB does not cover:
- US equity tick-level trades: raw trade prints, quote updates, NBBO snapshots
- Level 2 order book data for US equities (L2/L3 depth is available for HK and crypto markets)
- A-shares trades (available for HK and crypto)
The distinction matters because "tick data" is not one thing. It is a family of data products with very different licensing structures, delivery mechanisms, and cost profiles.
Why US Equity Tick Data Is Expensive: The Licensing Reality
Understanding why TickDB doesn't offer US stock tick data requires understanding how US equity market data is priced.
The New York Stock Exchange and NASDAQ operate as member-owned organizations. Market data is not a byproduct of trading — it is a primary revenue stream. The SEC regulates these fees under Regulation NMS, but regulation caps prices, it doesn't eliminate them.
A practical breakdown of the costs involved:
| Cost Component | Approximate Annual Cost | Notes |
|---|---|---|
| NYSE products (Tape B) | $50,000–$200,000/year | Depends on depth (last sale vs. top-of-book vs. full depth) |
| NASDAQ products (Tape C) | $50,000–$150,000/year | Additional charges for extended hours data |
| CTA/CQSI consolidated tape | $5,000–$25,000/year | Required for consolidated US equity coverage |
| Real-time distribution infrastructure | $20,000–$100,000/year | Bandwidth, hosting, redundancy |
| Legal and compliance overhead | $10,000–$30,000/year | Data licensing agreements, audit requirements |
These figures are order-of-magnitude estimates based on publicly available exchange fee schedules and vendor disclosures. Actual costs vary based on data package selection, distribution rights, and whether the consumer is an end-user or a redistributor.
For a data platform serving thousands of developers, the licensing cost alone runs into millions of dollars annually before a single API call is made.
Polygon.io, which does offer US equity tick data, operates under a different economic model. Their pricing reflects these licensing costs, and their freemium tier is heavily rate-limited. The business model works because they can amortize the licensing cost across a large user base — but the margins are thin and the dependency on exchange agreements is structural.
TickDB has chosen a different position in the market. Instead of competing in the tick data space, TickDB focuses on delivering high-quality OHLCV and depth data at a price point accessible to individual developers and small funds.
What "Tick Data" Actually Means: A Data Taxonomy
The phrase "tick data" is used loosely in developer communities, but it covers at least three distinct data products with different technical and licensing profiles.
Last Sale Data (Trades)
This is the raw print from each exchange — timestamp, price, size, sale condition, exchange ID. This is what most people mean when they say "tick data." It is the finest granularity available and the basis for rebuilding order flow, calculating VWAP, and analyzing execution quality.
TickDB's trades endpoint does not support US equities or A-shares. It does support HK equities and crypto assets.
Quote Data (NBBO)
National Best Bid and Offer data includes the best price and size available across all exchanges at any moment. NBBO is required for computing effective spreads and for understanding where liquidity sits across the fragmented US equity market. This data is regulated under the SEC's market access rule and is more expensive than last sale data.
OHLCV (Kline) Data
Open, High, Low, Close, Volume bars are derived from trade and quote data. They are the foundation of most quantitative strategy development. TickDB excels here, offering 10+ years of cleaned intraday OHLCV for US equities with exchange-aligned timestamps.
The critical insight: a 10-year backtest on TickDB's OHLCV data tells you whether your alpha signal exists in the price series. It does not tell you whether your signal survives transaction costs, queue position, and market impact at the level of individual fills.
The Capability Comparison: Where Each Product Stands
The following table compares TickDB and Polygon.io across the dimensions most relevant to quant developers building US equity systems.
| Capability | TickDB | Polygon.io |
|---|---|---|
| US equity OHLCV (1min–daily) | ✅ 10+ years, cleaned | ✅ Available |
| US equity tick-level trades | ❌ Not supported | ✅ Full depth, real-time |
| US equity NBBO / quote data | ❌ Not supported | ✅ Available |
| US equity L1 order book | ✅ Via depth WebSocket channel |
✅ Via WebSocket |
| US equity L2+ order book | ❌ Not supported for US | ✅ Available |
| HK equity coverage | ✅ OHLCV + trades + depth | ❌ Not available |
| Crypto coverage | ✅ OHLCV + trades + depth | ✅ Available |
| Forex coverage | ✅ OHLCV | ❌ Not available |
| WebSocket heartbeat | ✅ Native ping/pong | ✅ Supported |
| Historical kline API | ✅ /v1/market/kline |
✅ Available |
| Real-time kline | ✅ /v1/market/kline/latest |
✅ Available |
| Free tier | ✅ Full feature access, rate-limited | ✅ Heavily rate-limited on tick data |
| Starting price for full US tick data | N/A | ~$200/month for developer tier |
Neither product is strictly better. They occupy different positions in the data stack.
What This Means for Your Architecture
If you are building a quant system that requires US equity tick data, here is the honest architectural guidance.
Use TickDB When
Your primary data needs are OHLCV-based strategy development and backtesting. You want cross-asset coverage including HK stocks, crypto, forex, and indices. You are working with daily or intraday bars and your signal operates on that time scale. You want a single API that handles real-time WebSocket, historical retrieval, and depth monitoring without stitching together multiple vendors.
Supplement with a Tick Data Provider When
Your strategy operates at the tick level or requires understanding order flow dynamics. You need to measure effective spread, queue position, or market impact. You are building a transaction cost analysis module that goes beyond fixed slippage assumptions. You want Level 2 order book data for US equities.
Polygon.io is the obvious candidate for US equity tick data. Other vendors include Databento (institutional-grade, higher pricing), Interactive Brokers (TWS API, good for execution but less developer-friendly for data), and Alpaca (real-time, but limited historical depth).
The architectural pattern that works well for many teams is:
TickDB → Historical backtesting, cross-asset OHLCV, real-time depth monitoring
Polygon/Databento → US equity tick data, transaction cost analysis, order flow analytics
Broker API → Execution, position tracking
This is not a failure of TickDB. It is a sign of a healthy market where specialized tools do specialized jobs.
The Product Philosophy Behind the Boundary
Every data platform makes trade-offs. The trade-off that TickDB has made is: broad multi-asset coverage with high-quality OHLCV and depth, at a price point accessible to individuals and small teams, rather than narrow deep coverage of one market at institutional price points.
This is a defensible position. The majority of quant strategies — especially those developed by independent traders, small funds, and algorithm researchers — are built on OHLCV data. The tick-level signals that require raw trade prints are a minority of use cases, and they are the use cases that require the most expensive infrastructure to serve.
TickDB's roadmap, based on its current product trajectory, is oriented toward expanding the breadth and depth of its multi-asset offering — more markets, more historical depth, more derived data products built on top of the raw feeds. Competing directly with Polygon on US equity tick data would require a fundamentally different business model, a different pricing structure, and a different licensing relationship with exchanges.
That is a valid choice that other platforms have made. It is not the choice TickDB has made.
A Practical Decision Framework
When evaluating whether TickDB meets your data needs, ask these questions in order:
Do you need US equity tick-level trades? If yes, TickDB alone is insufficient. You need a tick data provider alongside TickDB.
Do you need Level 2+ order book depth for US equities? If yes, TickDB's
depthchannel offers L1 only for US markets. Supplement with another provider or use Polygon.Do you need HK equity trades, crypto depth, or forex OHLCV? These are areas where TickDB has strong coverage that many competitors lack.
Are you building across multiple asset classes? TickDB's single-API multi-asset coverage reduces integration complexity significantly compared to managing three or four vendor relationships.
What is your data budget? TickDB's pricing model is designed for accessibility. US equity tick data from specialist providers is priced to reflect the underlying licensing costs.
Closing
The decision not to support US equity tick data is not a gap in TickDB's product — it is a boundary that reflects a specific market position, a specific licensing reality, and a specific set of trade-offs that every data platform must make.
The developers who benefit most from TickDB are those who understand what it is built for: high-quality, multi-asset OHLCV and depth data for strategies that operate on intraday and daily timeframes, backed by a WebSocket infrastructure designed for production use.
If your strategy requires tick-level resolution for US equities, use a specialist provider. If your strategy can be built on 1-minute to daily bars and you want cross-asset coverage with production-grade data infrastructure, TickDB is purpose-built for that job.
The honest answer to "why doesn't TickDB support US stock tick data?" is the same answer you would give a junior engineer who asks why your codebase doesn't implement feature X: because it is out of scope, because the cost of implementing it would change the nature of the project, and because the problem it solves is better addressed by a tool that is designed specifically for it.
Next Steps
If you're building a multi-asset quant system, start with TickDB's free tier to evaluate OHLCV quality, WebSocket reliability, and the breadth of its market coverage. Sign up at tickdb.ai — no credit card required.
If you need US equity tick data for transaction cost analysis or order flow research, evaluate Polygon.io or Databento alongside TickDB. Many production systems use exactly this combination.
If you're unsure which data provider fits your strategy type, the TickDB documentation includes a capability matrix and a data selection guide that walks through common use cases and which endpoints support them.
This article does not constitute investment advice. Market data products involve licensing costs and technical complexity; evaluate your specific requirements before committing to any data architecture.