Validators process transactions and receive fees from users (supply-side fees).

Gnosis Chain is a smart contract platform for decentralized applications (a blockchain). Gnosis was founded by Martin Köppelmann and Stefan George and launched in 2015.

GNO holders own and govern the protocol. They currently take a cut of the total transaction fees paid by users (revenue). 

governance

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etherscan

website

Blockchains (L1)

Gnosis

# Gnosis Transactions per second Methodology

## 1. Overview

The transactions per second (TPS) metric measures the average number of transactions processed per second on the Gnosis blockchain on a daily basis. This metric provides insight into network activity and throughput by counting all distinct transactions within each day and converting the daily totals to a per-second average rate.

## 2. Data sources

- **Gnosis blockchain transactions**: Raw transaction records from the Gnosis blockchain containing transaction hashes, block timestamps, addresses, gas usage data, and transaction metadata
- **Account labeling data**: Address labels and titles for Gnosis chain accounts to categorize and enrich transaction destinations

## 3. Step-by-step calculation

### Component A: Raw transaction processing
- **Purpose**: Extract and standardize all Gnosis blockchain transaction data
- **Logic**: Pull all transactions from Gnosis blockchain records, including block timestamps, transaction hashes, from/to addresses, and gas information. Apply decimal corrections to gas price fields by dividing by 10^18 to convert from wei to standard units. Set the native token address to the wxDAI contract address and classify all transactions under the 'blockchains_l1' market sector and 'blockchain' business segment
- **Key fields**: `block_timestamp` (transaction timing), `transaction_hash` (unique identifier), `from_address` and `to_address` (transaction parties), `gas_used` and `effective_gas_price` (execution costs)

### Component B: Daily transaction aggregation
- **Purpose**: Count distinct transactions per day and enrich with address labels
- **Logic**: Group transactions by daily timestamp boundaries using timestamp truncation. For each day and destination address combination, count distinct transaction hashes to avoid double-counting. Join with account labeling data to categorize destination addresses, marking unlabeled addresses as 'Unlabeled' and labeled addresses with their corresponding titles
- **Key fields**: `timestamp` (daily boundary), `transaction_count` (distinct hash count), `contract_name` (address label or 'Unlabeled'), `to_address` (transaction destination)

### Final aggregation
- **Combining components**: Sum all transaction counts for each day across all destination addresses to get total daily transaction volume
- **Currency conversion**: Not applicable for transaction counting
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation, with each day representing a complete 24-hour period
- **Final calculation**: Divide the total daily transaction count by the number of seconds in a day (86,400) using safe division to calculate the average transactions per second for that day. Apply schema validation and gap-filling with zeros for missing data points to ensure consistent time series data

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Average confirmed user transactions added per second.

GnosisGNO

Transactions per second

Transactions per second

Competitive landscape