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Coinbase

GDAX (Coinbase)

Coinbase Historical Data

In 2015, Coinbase launched a crypto exchange called Coinbase Exchange.  They later rebranded this exchange to GDAX (which stood for Global Digital Asset Exchange).  GDAX became popular in part because it was one of the few exchanges where U.S. traders could trade bitcoin directly for fiat.

In 2018, the exchange was rebranded again, from Coinbase to Coinbase Pro, and promoted to active traders by offering advanced tracking and trading tools. Finally, in 2022-2023 Coinbase Pro was replaced by Coinbase Advanced Trade, which included all of Coinbase’s crypto services and added several new features, like staking. Coinbase Advanced now includes more than 550 trading pairs plus a host of technical indicators and charting tools. It's Coinbase’s offering for professional and advanced crypto traders and investors.

Amberdata’s Coinbase Crypto Market Data Features

We offer:

  • Coinbase time series data from 2014-12-01.
  • Historical tickers, tick-by-tick data, order book events, order book snapshots, OHLCV/candlesticks, trades.
  • We capture data that Coinbase itself does not store.
  • Our data formats are: 
    • REST API (historical time series)
    • WebSockets (real-time)
    • AWS S3 (bulk)
    • Snowflake
    • Google Cloud’s Analytics Hub
    • Databricks 
    • Downloadable by CSV through API docs

A Sample of Our Coinbase Market Data: 

Trades: Our trade datasets consist of all tick-by-tick trade data, timestamped, and with the trade direction normalized from the taker side. Our Trade endpoints provide historical (time series) trade data for the specified pair or instrument.

Order books: Order Book Snapshots, we collect via the exchanges REST API and the snapshot is a one minute snapshot. Every minute we get the full order book, full depth, from the exchange (as much as they provide). 

OHLCV: OHLCV is an aggregated form of market data standing for Open, High, Low, Close and Volume. OHLCV data includes 5 data points: the Open and Close represent the first and the last price level during a specified interval; High and Low represent the highest and lowest reached price during that interval; Volume is the total amount traded during that period. This data is most frequently represented in a candlestick chart, which allows traders to perform technical analysis on intraday values. 

Tickers: Tickers represent the best bids/asks from an orderbook. The bid price represents the maximum price that a buyer is willing to pay for an asset. The ask price represents the minimum price that a seller is willing to take for that same asset. We provide incremental tick-level updates/deltas of all bids and asks on an order book. This level 2 data is available within the Order Book endpoints.

Reference Quotes: Reference Quotes are calculated across all exchanges (or particular exchanges if specified) with a 1 second frequency, meaning we publish and update every second. It is derived from the Tickers data with the following calculation: Mid = (Ask + Bid) / 2). Our Reference Quote endpoint provides historical (time series) data for the specified pair and across all exchanges which support the pair. The data is available via REST API and is limited to 60 API requests per second.

VWAP: The volume-weighted average price (VWAP) is a measurement that shows the average price of an asset, adjusted for its volume over a given period of time. VWAP gives traders a smoothed-out indication of an asset’s price (adjusted for volume) over a given period of time. Institutional traders use VWAP to ensure that their trades do not move the price of the asset they are trying to buy or sell too extremely. Amberdata provides VWAP data aggregated minutely, hourly, or daily for all exchanges we cover, with historical data back to 2012 for some exchanges. Our VWAP endpoints are available via REST API for historical (time series) data as well as WebSockets for real-time data.

TWAP: TWAP (Time Weighted Average Price) is the average price that an asset is traded at during a specified time window, rather than its end-of-day price. It is an aggregated form of price data. Global TWAP uses time-weighted average price across all exchanges available for the asset. Amberdata provides TWAP data aggregated minutely, hourly, or daily for all centralized exchanges we cover, with historical data back to 2013 for some of the exchanges.

Prices: This section provides unweighted prices for every pair and asset across every exchange we support in the spot markets. You can view the data from the latest or historical endpoints. Depending on the exchange, we have data as far back as 2011. Our Prices endpoints are available via REST API for latest and historical (time series) data as well as WebSockets for real-time data.

Coinbase Trading Data

Via our endpoints, we offer a wide range of Coinbase trading data, such as event-level order book data, order book snapshots, trades, candles, and weighted and unweighted pricing. We provide metrics and aggregations at the asset, pair, and exchange level. We collect every executed transaction on GDAX (Coinbase); we poll at regular intervals to ensure that we are collecting every trade data point.

We normalize and standardize our datasets to prioritize quality, reliability, and ease of use.

Tickers API Endpoints

OHLCV API Endpoints

Order Books API Endpoints

Prices API Endpoints

TWAP API Endpoints

VWAP API Endpoints

Coinbase Historical Data

Amberdata’s Coinbase historical data consists of all tick-by-tick trade data, timestamped, and with the trade direction normalized from the taker side.  For GDAX (Coinbase) all of our historical data goes back to 2014-12-01, with the exception of Reference Quotes data, which goes back to 2019-02-25.  

As always, we normalize and standardize our datasets to prioritize quality, reliability, and ease of use.

Tickers API Endpoints

Trades API Endpoints

Order Books API Endpoints

OHLCV API Endpoints

Reference Quotes API Endpoints

VWAP API Endpoints

TWAP API Endpoints

Prices API Endpoints

Coinbase Reference Rates

Our Reference Rates provide benchmark prices for BTC and ETH, from select qualified exchanges, published both hourly and daily. These benchmarks comply with SOC I and II, align with GAAP, and adhere to the IOSCO Principles for Financial Benchmarks. Reference rate benchmarks support key initiatives for financial institutions including reporting, trading decisions, and contract settlements by reflecting a highly representative U.S. dollar value for specified digital assets. 

Amberdata's Reference Rates are accessible and relevant for users across the globe with the daily rate adjusted to the user's timezone. For example, an hourly reference rate calculated at 9 p.m. UTC will be marked as the 2 p.m. daily reference for PST users.

For more information about our reference rate methodology, download our Reference Rates whitepaper.

See Our Coinbase Market Data in Action with AmberLens

With AmberLens, our collection of institutional-grade digital asset metrics, you can analyze the historical and current market dynamics of Coinbase. AmberLens offers dashboards that empower you to enhance your portfolio by spotting and tracking market trends and comprehensively understanding the cryptoeconomy's overall performance.

Get started with Coinbase charts and dashboards in AmberLens here.

Coinbase Data Delivery & Distribution

Our Coinbase market data can be accessed via REST API for historical (time series) data and WebSockets for real-time data. 

For use cases that require large amounts of data such as backtesting, research, or reporting, we offer bulk downloads via Amazon Web Services, delivered in parquet and updated daily. Supported spot market data datasets include: 

  • Orderbook Snapshots and Events 
  • Tickers 
  • Trade Data
  • OHLCV

Data Delivery Partnerships and Marketplaces

Amberdata has partnered with Snowflake, Google Cloud’s Analytics Hub, and Databricks to make our datasets even more accessible for financial institutions.

These marketplaces and delivery partnerships streamline the process of accessing, querying, and visualizing data, enabling your team to uncover insights quickly.

Explore Market Data Coverage for More Supported Exchanges

Coinbase Historical Data Use Cases

Financial institutions entering the crypto space will find Coinbase's historical data incredibly useful for making strategic decisions and assessing risk. This data gives you a clear view of market trends, helping you understand what's happening in the crypto world. You can use this to predict where the market is headed, perfect your trading strategies, and spot patterns to improve your investment choices. Plus, you can feed this data into machine learning models for predictive analysis, allowing you to stay ahead of market changes and adjust your strategy as needed. 

Coinbase historical data is also an invaluable tool for testing trading strategies. It gives traders a solid framework to tweak and perfect their strategies before they go live. How? By simulating trades using historical data. This lets traders see how their strategies would have performed under past market conditions, find any potential weak spots, and make the necessary changes. This process helps reduce risk, increase trading efficiency, and boost the overall performance of your portfolio.