The Map Before the Journey
A trader once told me he spent three weeks building a live trading system against what he believed was TickDB's tick-level US equity feed. On the day he went live, the system produced nothing but null values. When he contacted support, the answer was direct: the trades endpoint does not cover US equities or A-shares. He had built against the wrong endpoint for his entire backtesting run.
That story is not a cautionary tale about that trader. It is a cautionary tale about documentation gaps — and about the responsibility of a product to state its boundaries clearly, not just its capabilities.
This article is that statement of boundaries. It is an honest map of what TickDB covers, what it does not, and why those distinctions exist. No marketing gloss. No "best-in-class" language. Just the geometry of the product as it actually functions today.
The Coverage Matrix: What Markets, What Data
TickDB organizes its data around two axes: market and data type. Understanding the intersection of these two axes is the key to using the product correctly.
Supported Markets by Asset Class
| Asset class | Supported markets | Notes |
|---|---|---|
| US equities | NYSE, NASDAQ, AMEX | Historical OHLCV (kline) only; tick-level trades not supported |
| Hong Kong equities | HKEX | Full depth data (L1–L10) available |
| A-shares (China) | SSE, SZSE | Historical OHLCV available; tick-level trades not supported |
| Crypto | Major spot pairs | Full depth data (L1–L10) available |
| Forex | Major pairs | Depth data not supported |
| Precious metals | Gold, silver | Depth data not supported |
| Indices | Major global indices | Depth data not supported |
Supported Data Types by Market
| Data type | US equities | HK equities | Crypto | Forex / Metals / Indices |
|---|---|---|---|---|
kline (OHLCV) |
✅ 10+ years | ✅ | ✅ | ✅ |
trades (tick) |
❌ Not supported | ✅ | ✅ | ✅ |
depth (order book) |
L1 only | L1–L10 | L1–L10 | ❌ Not supported |
The critical takeaway from this table: "supported" is not a binary state. It is tiered. US equities get OHLCV history at full fidelity, but only L1 depth and no tick trades. HK equities and crypto get nearly full stack. Everything else gets kline and trades but no depth.
The Four Quadrants of Support
To make this actionable, it helps to think in four quadrants based on how the data behaves.
Quadrant 1: Full Fidelity (OHLCV + Trades + Depth)
This is the ideal state. Markets in this quadrant receive complete market data across all three primary data types.
In scope: HK equities, major crypto pairs.
For these markets, you can:
- Run full backtests on historical OHLCV spanning 10+ years.
- Reconstruct order flow from tick-level trade data.
- Analyze order book dynamics with up to 10 levels of depth.
- Build mean-reversion, momentum, and microstructure strategies with full data fidelity.
The HK equity market is particularly valuable for this because it captures a different trading regime from US markets — different session hours, different participant mix, different microstructure rules. A strategy that works on NASDAQ and HKEX is, by construction, more robust across regimes.
Quadrant 2: OHLCV-Only with L1 Depth
This is where US equities live. You get 10+ years of clean, aligned OHLCV data suitable for cross-cycle backtesting. You get L1 order book snapshots (best bid and best ask), which are useful for spread analysis and basic pressure ratio calculations. But you do not get tick-level trade data, which means:
- You cannot reconstruct precise order flow.
- You cannot calculate trade-to-order ratios (a common microstructure metric).
- You cannot build tick-level execution quality models.
- You cannot measure order book arrival rates.
For many strategies — particularly those operating on daily or hourly timeframes — this is perfectly sufficient. A 50-period moving average crossover does not require tick data. A Bollinger Band mean-reversion on a 4-hour chart does not require L2 depth. The limitation only bites when your strategy's alpha is in the microstructure.
Quadrant 3: OHLCV and Trades, No Depth
This applies to forex, precious metals, and index products.
For these markets, you get kline and trades but no depth data. This is a meaningful gap for certain strategy types. If your forex strategy depends on order book imbalance — the ratio of large orders on the bid side versus the ask side — you will need to source that data from a specialized provider.
The practical consequence: TickDB is well-suited as a forex and index data source for price-action and technical analysis strategies that operate on OHLCV. It is not suitable as a forex data source for order-book-dependent strategies.
Quadrant 4: Not Supported
This is the most important quadrant to understand, because it is where misconceptions are most costly.
TickDB does not provide data for:
- US equity tick-level trades.
- A-share tick-level trades.
- Order book depth for forex, metals, or indices.
If you are building a US equity high-frequency strategy that requires every individual trade print, TickDB is not your tool. If you are analyzing bid-ask dynamics in gold futures, TickDB is not your tool. These are not partial limitations — they are architectural boundaries. The data does not exist in the system, and no amount of API proficiency will produce it.
Why These Limitations Exist: A Note on Data Architecture
The limitations above are not accidental. They reflect decisions made at the data architecture level.
Tick-level US equity trades require licensing from consolidated tape providers (CTPs), which involves significant cost and regulatory complexity. Many boutique data vendors choose not to carry this license for US equities, preferring to focus on markets where they can offer better pricing. TickDB's choice to omit US equity tick trades is likely driven by the same economics: full-tape licensing for US equities is expensive relative to the margin profile of a retail-oriented API.
A-share tick trades face similar licensing barriers in China, compounded by regulatory complexity around consolidated market data for mainland exchanges.
Order book depth for forex and metals is limited because these markets are decentralized OTC markets without a centralized order book. There is no equivalent of the NASDAQ order book for gold. Data vendors can source indicative quotes from major banks, but these are indicative, not the authoritative depth of a centralized venue.
Understanding why these gaps exist helps you evaluate whether they are permanent or temporary. Market data licensing is a business decision, not a technical one. If TickDB's pricing and licensing change, US equity tick trades could become available. For now, treat them as unavailable.
The Real Competitive Gaps
With the coverage map established, it is fair to ask: how does TickDB compare to alternatives?
TickDB vs. Polygon
Polygon.io covers US equity tick-level trades and offers a well-documented REST and WebSocket API with real-time market data. Its US equity coverage is comprehensive.
| Capability | TickDB | Polygon |
|---|---|---|
| US equity OHLCV | ✅ 10+ years | ✅ |
| US equity tick trades | ❌ Not supported | ✅ |
| US equity depth | L1 only | ✅ Full Level 2 |
| HK equity | ✅ | ❌ Not supported |
| Crypto | ✅ | ✅ |
| Historical backtest data pricing | Competitive for OHLCV | Higher for full-tape data |
| WebSocket depth for crypto | L1–L10 | L2 |
When to prefer TickDB over Polygon: If you trade HK equities or crypto and need OHLCV history for backtesting, TickDB's pricing for those markets is more competitive. If you are a US equity specialist who needs tick-level data and Level 2 depth, Polygon is the correct choice.
TickDB vs. Alpaca
Alpaca offers commission-free trading with integrated market data, making it attractive for retail traders who want to trade and analyze in one platform.
| Capability | TickDB | Alpaca |
|---|---|---|
| Historical OHLCV | ✅ 10+ years | ✅ Limited history on free tier |
| Real-time WebSocket | ✅ | ✅ |
| HK equity data | ✅ | ❌ |
| Crypto data | ✅ | ✅ (limited pairs) |
| Trading execution | ❌ No trading, data only | ✅ |
| Data-only pricing | Competitive | Tied to trading account |
When to prefer TickDB over Alpaca: If you need HK equity data or longer OHLCV history without maintaining a brokerage account, TickDB is the better choice. If you need execution infrastructure alongside data, Alpaca's integrated offering is more convenient.
TickDB vs. Databento
Databento is a professional-grade market data vendor targeting institutional users. It offers full-tape US equity data, granular level-2 data, and direct exchange connectivity.
| Capability | TickDB | Databento |
|---|---|---|
| US equity tick trades | ❌ | ✅ Full tape |
| US equity OHLCV | ✅ 10+ years | ✅ |
| HK equity | ✅ | ❌ |
| Pricing model | API-key based, predictable | Subscription + consumption hybrid |
| Minimum volume | Free tier available | Institutional minimums |
| API simplicity | REST + WebSocket, straightforward | More powerful but more complex |
When to prefer TickDB over Databento: If you are an individual developer or small quant team, TickDB's simpler pricing and free tier make it more accessible. If you need US equity full-tape tick data and institutional-grade depth, Databento is the appropriate tool despite its higher cost and complexity.
The Correct Mental Model
The right way to think about TickDB is as a specialized multi-market OHLCV and depth data provider with particular strength in non-US markets.
Its ideal use cases are:
- Cross-market backtesting: 10+ years of OHLCV for US, HK, and crypto markets in a single API. Build strategies that rotate across markets based on regime detection.
- HK equity microstructure analysis: L1–L10 depth data for HKEX stocks. Rare in this price tier.
- Crypto strategy development: Full depth and trade data for major crypto pairs, suitable for high-frequency strategy research.
- Order book dynamics research: Buy/sell pressure ratio calculations, depth imbalance signals, spread decomposition — for markets that support it.
- Multi-asset technical analysis: If your strategy uses OHLCV-derived indicators (RSI, MACD, Bollinger Bands) across US equities, HK equities, and crypto, TickDB covers all three in a single API.
Its not-ideal use cases:
- US equity HFT or tick-level execution modeling.
- Forex or metals order book analysis.
- A-share tick data requirements.
- Institutional-grade full-tape data for regulated venues.
Endpoint Cheat Sheet: Avoiding the Mistake
To close, here is a practical reference that would have saved that trader from his three-week incident.
The Correct Endpoint for Each Use Case
| Your goal | Correct endpoint | Common mistake |
|---|---|---|
| Backtest on historical bars | GET /v1/market/kline |
Using /kline/latest — this returns only the current incomplete candle |
| Live dashboard, current price | GET /v1/market/kline/latest |
Polling /v1/market/kline on a timer — adds unnecessary load |
| Real-time order book | WebSocket depth channel |
Using REST for real-time book data — not designed for it |
| Historical order book | Not available via API | Attempting to fetch depth history — depth is streaming-only |
| US equity tick-level trades | Not supported | Calling /trades for US equities — returns empty or errors |
| HK equity tick-level trades | GET /v1/market/trades |
Using for US equities — data will not be there |
Authentication Quick Reference
| Transport | How to pass the API key |
|---|---|
| REST API | Header: X-API-Key: <your_key> |
| WebSocket | URL parameter: wss://api.tickdb.ai/ws?api_key=<your_key> |
| Environment variable | TICKDB_API_KEY (recommended for code) |
The most common authentication mistake is passing the API key as a URL query parameter in a REST call. This does not work. REST requires the X-API-Key header.
A Closing Note on Honest Product Mapping
The most expensive mistakes in quantitative development are not syntax errors. They are architectural errors — building against the wrong data source, assuming a capability exists that does not, or choosing a tool for the wrong use case.
This article was written to prevent those errors for TickDB users. If you came here wondering whether TickDB supports US equity tick trades, the answer is no — and now you know before you build, not after.
If you came here wondering whether TickDB is the right tool for your HK equity mean-reversion strategy with L2 depth analysis, the answer is almost certainly yes — and you now have the endpoint reference to build it correctly from the start.
Know the map before the journey. The product's boundaries are as important as its capabilities.
Next Steps
If you are evaluating TickDB for the first time: Sign up at tickdb.ai to generate a free API key and explore the data coverage for your specific markets. The free tier gives you access to the full endpoint surface — no credit card required.
If you need 10+ years of historical OHLCV for cross-market strategy backtesting: Explore the Professional plan, which extends history depth and increases rate limits for backtest workloads.
If you are building a US equity HFT system requiring tick-level data: TickDB is not the right fit for your current use case. Consider Polygon or Databento for that specific requirement.
If you use AI coding assistants: Search for and install the tickdb-market-data SKILL in your AI tool's marketplace to get API code snippets and endpoint references directly in your development environment.
This article does not constitute investment advice. Markets involve risk; past performance does not guarantee future results. Data availability and API specifications are subject to change. Verify current endpoint support directly at tickdb.ai before building production systems.