Forex API
Tick-level quotes for 50+ currency pairs including majors, minors and exotics.
Stream tick-level Forex, Crypto, Stock, Commodity and Index data over a single WebSocket and REST API. Get a free key in seconds — no sales call required.
| Symbol | Asset class | Price | Latest move |
|---|---|---|---|
| EUR/USD ForexEuro / US Dollar | Forex | - | - |
| BTC/USDT CryptoBitcoin | Crypto | - | - |
| ETH/USDT CryptoEthereum | Crypto | - | - |
| AAPL StockApple Inc. | Stock | - | - |
| XAU/USD CommodityGold Spot | Commodity | - | - |
| USD/JPY ForexUS Dollar / Yen | Forex | - | - |
| NVDA StockNVIDIA Corp. | Stock | - | - |
| SPX IndexS&P 500 Index | Index | - | - |
Every market AllTick covers is available through the same unified REST and WebSocket interface.
Tick-level quotes for 50+ currency pairs including majors, minors and exotics.
Real-time spot and derivatives data, normalized into one feed.
Equities across US, Hong Kong and mainland China with trades and quotes.
Live pricing for precious metals and energy.
Benchmark index values and constituents for major global indices.
Compare coverage, latency and data types across every AllTick market.
Browse productsHow AllTick compares to a typical legacy market-data vendor.
| Capability | AllTick | Typical Legacy Vendor |
|---|---|---|
| Median WebSocket latency | ~150ms | 400–800ms |
| Asset classes in one API | 5 (FX, Crypto, Stock, Commodities, Indices) | 1–2 |
| Uptime SLA | 99.95% | 99.5% or none |
| Free tier | Yes — instant API key | Sales call required |
| WebSocket streaming | Native | Polling / limited |
Connect over WebSocket and subscribe to any symbol across any market.
# AllTick realtime financial data API
# forex crypto stock commodities indices
import asyncio, json, uuid
import websockets
subscribe = {
"cmd_id": 22004,
"seq_id": 1,
"trace": str(uuid.uuid4()),
"data": {"symbol_list": [{"code": "EURUSD"}]},
}
heartbeat = {"cmd_id": 22000, "seq_id": 1, "trace": "heartbeat", "data": {}}
async def stream():
uri = "wss://quote.alltick.co/quote-b-ws-api?token=YOUR_API_KEY"
async with websockets.connect(uri) as socket:
await socket.send(json.dumps(subscribe))
async def keep_alive():
while True:
await asyncio.sleep(10)
await socket.send(json.dumps(heartbeat))
asyncio.create_task(keep_alive())
async for message in socket:
print(json.loads(message))
asyncio.run(stream())Cut market-data costs by 60% while adding crypto coverage.
“Migrating to AllTick let us consolidate three vendors into one WebSocket feed and ship our trading app a quarter early.”Read case study
Served 40k concurrent users with sub-200ms quote updates.
“The 99.95% SLA and consistent latency were exactly what our retail brokerage needed to scale globally.”Read case study
Backtested 12 years of tick data across 5 asset classes.
“Having historical and live data from a single normalized API removed weeks of data-engineering work.”Read case study
Generate a free API key in seconds and connect to every market from one endpoint.
Practical writing on market data engineering, streaming APIs and building low-latency financial applications.
Generate a free API key in seconds and connect to every market from one endpoint.

In real-time forex trading systems, subscribing to multiple currency pairs seems like a simple scalability feature. However, once deployed in production, a subtle but critical issue quickly emerges: data out-of-order delivery. Especially in
In real-time forex trading systems, subscribing to multiple currency pairs seems like a simple scalability feature. However, once deployed in production, a subtle but critical issue quickly emerges: data out-of-order delivery.
Especially in high-frequency streaming scenarios—such as simultaneously subscribing to EURUSD, GBPUSD, and USDJPY—you will find that data within the same time window does not arrive in strict chronological order. Instead, it is affected by network latency, server-side parallelism, and client-side scheduling.
At first glance, it looks like a minor sequencing issue. But in trading systems, it can directly impact:
At its core, this is not a “data problem”, but a consistency problem in streaming systems.
In most Forex APIs, real-time WebSocket design follows a “single connection, multiple subscriptions” model:
For example:
These streams are generated in parallel on the server side but merged into a single message stream on the client side.
This creates a fundamental issue:
Multiple independent timelines are forced into a single-threaded message queue.
As a result, data order becomes unreliable.
Out-of-order delivery typically comes from four layers:
TCP guarantees reliability, not business-level ordering.
Packets may:
Result: later-generated data may arrive earlier.
Market data servers are typically multi-threaded:
Publishing is merged into a queue, not strictly time-sorted.
In Python/Node.js WebSocket clients:
Thus:
Arrival order ≠ generation order ≠ timestamp order
A naive implementation often uses:
All symbols → one on_message → one queue
This destroys structural ordering entirely.
Out-of-order data is not just cosmetic—it breaks trading logic:
For 1-second candles:
Result: OHLC values become incorrect.
Short-term strategies rely on sequence:
If order is broken:
Momentum signals become noise-contaminated.
If quote updates are misordered:
The key is not to “prevent disorder”, but to:
Reconstruct deterministic order on the client side.
Three key fields are used:
Never mix all symbols into one queue:
streams = {
"EURUSD": Queue(),
"GBPUSD": Queue(),
"USDJPY": Queue()
}
Each currency pair maintains its own timeline.
Use a short buffer per symbol:
BUFFER_MS = 200
Logic:
If API provides seq_id:
last_seq = {}
def check_order(symbol, tick):
seq = tick["seq"]
if symbol not in last_seq:
last_seq[symbol] = seq
return True
if seq > last_seq[symbol]:
last_seq[symbol] = seq
return True
return False
This filters most replay or delayed packets.
A more realistic multi-symbol structure:
import websocket
import json
import uuid
import time
from collections import defaultdict, deque
API_KEY = "YOUR_API_KEY"
WS_URL = f"wss://quote.alltick.co/quote-b-ws-api?token={API_KEY}"
SYMBOLS = ["EURUSD", "GBPUSD", "USDJPY"]
buffers = defaultdict(deque)
last_seq = {}
def subscribe_msg():
return {
"cmd_id": 22004,
"seq_id": int(time.time()),
"trace": str(uuid.uuid4()),
"data": {
"symbol_list": [{"code": s} for s in SYMBOLS]
}
}
def on_open(ws):
ws.send(json.dumps(subscribe_msg()))
def process_tick(symbol, tick):
seq = tick.get("seq")
if seq is not None:
if symbol in last_seq and seq <= last_seq[symbol]:
return
last_seq[symbol] = seq
buffers[symbol].append(tick)
def on_message(ws, message):
msg = json.loads(message)
if msg.get("cmd_id") == 22998:
tick = msg["data"]
symbol = tick["code"]
process_tick(symbol, tick)
def start():
ws = websocket.WebSocketApp(
WS_URL,
on_open=on_open,
on_message=on_message
)
ws.run_forever(ping_interval=10)
if __name__ == "__main__":
start()
Compared to crypto markets, forex APIs have unique characteristics:
Quotes come from multiple LPs
EURUSD vs exotic pairs behave very differently
Asian / London / US sessions
Result:
Data behaves like intermittent bursts, not continuous flow.
Advanced systems go beyond reordering:
Not arrival-time, but event-time
Allow bounded lateness:
Align multiple instruments into a unified time framework
Once ordering issues are properly handled, market data transforms:
What emerges is no longer a raw data stream, but a structured temporal system:
On top of this foundation, trading systems—whether market making, arbitrage, or risk control—can operate reliably.
And infrastructures like AllTick API provide not just market data, but an engineering-grade real-time time-stream layer.
Generate a free API key in seconds and connect to every market from one endpoint.