What happened
The analytics platform has added data from Binance and Coinbase exchanges, covering the most liquid pairs with Bitcoin and Ethereum.
Why it matters
Access to aggregated orderbook data allows market participants to assess real liquidity and potential support or resistance levels without the need for manual data collection from each exchange individually.
Analytics firm Glassnode Research announced the launch of new aggregated orderbook metrics for spot markets. This feature became available to platform users in late June 2026.
In the initial phase, data coverage is limited to two major exchanges: Binance and Coinbase. The system tracks conditions exclusively for the most liquid trading pairs, including Bitcoin (BTC) and Ethereum (ETH).
The publication of this information represents an update to data collection methodology, enabling observation of market depth on key venues in near real-time.
Confirmed facts
- Glassnode Research launched aggregated spot orderbook metrics.
- Initial coverage includes Binance and Coinbase exchanges.
- Data is available for the most liquid BTC and ETH pairs.
- Information was published on June 23, 2026.
Context
An orderbook displays all current buy and sell orders for an asset at various prices. Aggregating this data from multiple exchanges helps smooth out local liquidity anomalies and provides a more complete picture of market conditions.
What remains unknown
- Does Glassnode plan to add support for other exchanges or less liquid trading pairs in the future?
- Will these metrics be available in the free tier or only for premium subscribers?
- How exactly are aggregated values calculated given differences in data structures across different exchanges?
AI analysis
Confidence: low
The launch of this tool indicates a drive by analytics services to deepen transparency of market microstructure for institutional clients. The focus solely on BTC and ETH suggests that the data provider prioritizes assets with the highest trading volumes, where orderbook depth analysis holds maximum practical value for large players.
Strategic AI conclusion
A likely consequence will be increased use of this data by professional traders to calibrate trade execution algorithms. The next observable signal should be an expansion of the list of supported exchanges or the appearance of historical retrospectives. The main uncertainty remains the impact of this data on volatility if a large number of participants begin reacting to the same liquidity levels simultaneously.