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Crypto microstructure metrics and raw data

Point-in-time metrics built from hundreds of terabytes of raw data, and now the raw trades, quotes and derivatives data too. Pull both as Parquet files.

no key needed for either
>>>ap.stream()install
$ pip install "aperiodic[stream]"
python
import os
import aperiodic as ap

ap.stream(
    api_key=os.environ["APERIODIC_API_KEY"],
    channels=[
        {"dataset":"ohlcv","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"l1_liquidity","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"l2_imbalance","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"l2_liquidity","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"flow","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"trade_size","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"returns","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"slippage","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"impact","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"open_interest","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"funding","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
        {"dataset":"basis","exchange":"binance-futures","interval":"1m","symbols":["perpetual-BTC-USDT:USDT"]},
    ],
)
No key needed: here, Run streams the public tape, 15 minutes behind. With a key on a Live plan, stream() has no delay.
>>>ap.get_metrics()install
$ pip install "aperiodic[polars]"
python
from datetime import date
import aperiodic as ap

df = ap.get_metrics(
    metric="flow",
    exchange="binance-futures",
    symbol="perpetual-BTC-USDT:USDT",
    interval="5m",
    timestamp="exchange",
    start_date=date(2025, 5, 1),
    end_date=date(2025, 5, 31),
    preview=True,
)
No key needed: here, Run fetches the free preview, BTC-USDT on Binance in 5m bars for May 2025. With a key, get_metrics() fetches any contract we cover, over any range.

Shown: minute lows of every Binance perpetual, 20:40–22:00 UTC on 10 Oct 2025 · built with ohlcv 1mRead the full replay →

Why Aperiodic

One API

Metrics and raw data, without the infrastructure

Microstructure metrics and the raw trades, quotes and derivatives data behind them, through one unified API. No tick pipelines, storage clusters or recalculation jobs to maintain.

History

5 years of history on a monthly subscription

Prime unlocks 5 years of history on a monthly plan, no annual contract. Immutable data, no periodic re-calculations.

Access

No rate limits

Unthrottled API on Prime. Your crypto data lake as Parquet files, downloaded in 2 commands.

Timestamps

Local timestamped

Metrics with both exchange & local timestamps.

Coverage

Full coverage

Every instrument, no survivorship bias.

Pull your first dataset today.

Get Started

How It Works

Exchanges

Binance
OKX
Hyperliquid
+ more
Aperiodic
01ValidateQA & Deduplication
02TimestampLocal + Exchange Times
03NormalizeOne Schema, Same Symbols
Point-in-Time · Immutable · 99.9% Uptime
Aggregate
Metrics
Trades / Order Flow
Trades / Order Flow
Flow Toxicity·Taker Volume·Size Distribution
L1 (Top of Book)
L1 (Top of Book)
Spreads (bps)·Imbalance·Depth at Best
L2 (Depth)
L2 (Depth)
Multi-Level Profiles·Book Imbalance·Liquidity
Derivatives
Derivatives
Funding Rates·Open Interest·Basis Spreads
Market
Market
OHLCV·TrueOHLCV·High-Freq Volatility
Trades
Trades
Every Print·Trade ID·Taker Side
Quotes
Quotes
Top of Book·Bid & Ask Sizes·Every Change
Derivatives
Derivatives
Mark & Index Price·Funding·Open Interest
Raw dataPrime + Raw

Exchanges

Binance
OKX
Hyperliquid
+ more
Aperiodic
01ValidateQA & Deduplication
02TimestampLocal + Exchange Times
03NormalizeOne Schema, Same Symbols
Point-in-Time · Immutable · 99.9% Uptime
Raw dataPrime + Raw
Trades
Every Print·Trade ID·Taker Side
Quotes
Top of Book·Bid & Ask Sizes·Every Change
Derivatives
Mark & Index Price·Funding·Open Interest
Aggregate
Metrics
Trades / Order Flow
Flow Toxicity·Taker Volume·Size Distribution
L1 (Top of Book)
Spreads (bps)·Imbalance·Depth at Best
L2 (Depth)
Multi-Level Profiles·Book Imbalance·Liquidity
Derivatives
Funding Rates·Open Interest·Basis Spreads
Market
OHLCV·TrueOHLCV·High-Freq Volatility

What will you use it for?

Improve your backtest

Stop backtesting fantasy fills. Price in slippage, impact and funding with point-in-time metrics.

2 notebooks

Find new alpha

From raw order flow to a ranked, backtestable signal — every step in runnable code.

3 notebooks

Execute smarter

Know when liquidity is deep, when spreads are wide, and when flow turns toxic.

2 notebooks

Shown: 10 Oct 2025 UTC, minute by minute: the lows of the 465 Binance perpetuals, BTC’s in ink; net taker flow summed over Binance, OKX and Hyperliquid; OKX’s median book depth as a share of normal; each with its extreme in orange · built with ohlcv, flow and l2_liquidity 1m

Beyond Price & Volume

Open the markets dashboard

Most market data stops at price and volume. These are the 8 most traded perpetuals right now, each across its venues, with the order-book and order-flow metrics Aperiodic computes beside them.

15 min delayedLoading the newest bar…

PricePrice & volumeMicrostructureover the last 24h
AssetPrice24h%Volume 24hSpreadbpsToxicitySlippagebpsBuy/sell24h
  • SpreadbpsWhat it costs to cross the book: the median gap between best bid and ask.
  • ToxicityWhether one-sided taker flow comes with price moves, a sign of informed trading.
  • SlippagebpsHow far market orders filled from the quote, on average.
  • Buy/sellTaker buying against taker selling. Above 1, buyers lead.

Metric Catalog

Browse catalog

Slippage

Pro

How much each trade pays above the best ask (buys) or receives below the best bid (sells) relative to the prevailing quote, aggregated per interval.

Key fields

Mean Slippage (bps)Slippage Std Dev (bps)Slippage P95 (bps)VWAP Slippage (bps)

L2 Order Book Imbalance

Prime

Multi-depth (5, 10, 20, 25 levels) order book imbalance, ratio, and averages.

Key fields

Imbalance (5 levels)Imbalance (20 levels)Imbalance (25 levels)Imbalance Ratio (5 levels)

L1 Price

Pro

Best bid and ask prices with quantities, midprice, quantity-weighted midprice, time/volume-weighted averages, and quote update frequency.

Key fields

Mid PriceWeighted Mid PriceBid Price TWAPAsk Price VWAP

Trade Run Structure

Pro

Consecutive same-direction trade run lengths, imbalance, flip rate, and price change on direction flip.

Key fields

Max Buy Run LengthMax Sell Run LengthRun ImbalanceFlip Rate

Impact Metrics

Pro

How much each unit of trading volume moves the price, measured via Amihud illiquidity, Kyle lambda, impact per notional, and large-trade reversal.

Key fields

Amihud IlliquidityKyle LambdaImpact per NotionalLarge Trade Reversal

Flow Metrics

Pro

Directional order flow split by taker buy vs. sell, broken into small/medium/large notional segments, with a flow toxicity score.

Key fields

Volume DeltaFlow Toxicity ScoreBuy/Sell RatioBuy Large Order Volume

VWAP / TWAP

Pro

Volume-weighted and time-weighted average prices for precise execution benchmarks.

Key fields

VWAPTWAP
Discover the full catalog

Raw Data Catalog

See raw data
The trades, quotes and derivatives ticks behind the metrics, for Binance, OKX and Hyperliquid perpetuals. Same API key, same symbols, one Parquet file per month of history and per day since August 2026. In the Prime + Raw plan.

Trades

Every print. Binance, OKX and Hyperliquid

Datasets

  • trades

Quotes

Top of book. Binance, OKX and Hyperliquid

Datasets

  • quotes

Derivatives

Mark, index, funding and open interest. Binance, OKX and Hyperliquid

Datasets

  • mark_price
  • index_price
  • funding_rate
  • open_interest
terminal
# Install the Aperiodic CLI into ~/.local/bin
mkdir -p "$HOME/.local/bin"
curl -fsSL https://raw.githubusercontent.com/aperiodic-io/cli/main/install.sh | INSTALL_DIR="$HOME/.local/bin" bash
export PATH="$HOME/.local/bin:$PATH"

# Download the 2025-06 trades file into ./raw — no API key needed
aperiodic raw trades --preview \
  --exchange binance-futures \
  --symbol perpetual-BTC-USDT:USDT \
  --output-dir ./raw && echo "Saved to $PWD/raw"
Coverage, schemas and a free sample

Trusted by Professional Traders

Unsigned ResearchCorvus ResearchRobotWealthXlydian

Trusted by further institutional partners under confidentiality

Use Cases

Order Flow

Order flow alpha signals

Build directional signals from taker buy/sell imbalance, volume delta, and flow toxicity scores across multiple horizons.

Market Data

Systematic strategy backtesting

Build and validate momentum, mean-reversion, and carry strategies on reliable price history without data leakage.

Derivatives

Funding rate regime analysis

Detect crowded positioning and carry opportunities by monitoring funding rate levels and predicted-vs-realized spread dynamics.

Order Book

Deep liquidity analysis

Measure aggregate bid and ask depth at multiple levels to understand resilience and liquidity beyond the top-of-book.

Top of Book

Spread-based execution cost modelling

Use average and instantaneous spread metrics to quantify market-making costs and estimate fill quality across instruments.

Order Flow

Market impact modelling

Estimate Amihud illiquidity, Kyle lambda, and impact-per-notional for realistic transaction cost models in backtests.

Order Book

Order book imbalance signals

Build predictive features from multi-level imbalance ratios that capture directional pressure more robustly than L1 alone.

Top of Book

High-frequency strategy feature engineering

Use weighted mid-price, imbalance averages, and depth to build predictive features for HFT and MM strategies.

Open-Source Toolkit

View on GitHub
Free tools to use alongside Aperiodic data, or on their own. Atlas, our crypto security master, gives every spot, perpetual and futures contract on Binance, Bybit, OKX and Hyperliquid one normalized ID, and it is the symbology every Aperiodic symbol uses.
Atlas · Security master

One name for every crypto instrument

  • Binancebtcusdt
  • BybitBTCUSDT
  • OKXBTC-USDT-SWAP
perpetual-BTC-USDT:USDT
  • 17,000+ instruments
  • 11,000+ delisted, with end dates
  • Refreshed daily
  • MIT licensed
Why a free security master matters

Order Flow & Liquidity Metrics Without the Infrastructure

Professional traders and quant researchers use Aperiodic to go from raw exchange data to actionable metrics in minutes — not months.

Browse CatalogSchedule a Chat

Shown: the deepest drop of every perpetual on Binance, OKX and Hyperliquid, 20:50–22:00 UTC on 10 Oct 2025, one tile each, three blocks in that order, deepest first; IOTX at −94.8%, the deepest of the 847, is the one orange tile · built with ohlcv 1m

Aperiodic

Microstructure, liquidity & order flow metrics for crypto perpetuals.

Built from hundreds of terabytes of raw data and distilled into point-in-time metrics you can pull as parquet files. Plus the raw trades, quotes and derivatives data behind them.

Get startedBook a call
Use Cases
  • Improve your backtest
  • Find new alpha
  • Execute smarter
Catalog
  • Full Catalog
  • Markets
  • Order Flow
  • L1 — Top of Book
  • L2 — Order Book
  • Market Data
  • Derivatives
  • Raw Data
  • RWA
  • Atlas Security Master
Developers
  • API Docs
  • Notebooks
  • For AI Agents
  • Changelog
  • Roadmap
  • llms.txt
Learn
  • Replays
  • Microstructure Guide
  • Research Blog
  • FAQ
Compare
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  • vs. Amberdata
Company
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  • Contact
  • Book a call
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  • Licensing
  • SLA

© Copyright 2026 Aperiodic. All Rights Reserved.

Aperiodic Limited · Registered in Ireland · Company No. 815273 ·
136 Capel Street, Dublin D01 T2C9, Ireland

Shown: minute closes of 847 perpetuals, 20:30–22:30 UTC on 10 Oct 2025, IOTX in orange · built with ohlcv 1m