News Report Technology
August 08, 2025

TON Dataset Now Available On AWS Public Blockchain Platform For Enhanced Analytics

In Brief

TON has made its comprehensive blockchain dataset available on AWS, providing researchers and developers with free access to detailed transaction, token, NFT, and decentralized exchange data for advanced analysis and innovation.

Accessible TON Blockchain Dataset on AWS Enables Advanced Insights into Transactions, NFTs, and Decentralized Trading

Decentralized layer 1 blockchain The Open Network (TON) announced that its dataset is now accessible on the Amazon Web Services (AWS) public blockchain dataset platform. This offering grants researchers, developers, and analysts free access to extensive data from the TON blockchain, facilitating advanced analytics and research to support innovation within the blockchain ecosystem.

The dataset is produced by the TON-ETL project, created by TON Studio, a team focused on supporting developers in the TON ecosystem. Hosted on AWS, the project utilizes various services including Amazon S3, Amazon RDS, Amazon Athena, and Amazon EKS to ensure reliable data storage, processing, and analysis. Data is stored in Parquet format on Amazon S3 and partitioned by date to enhance query efficiency, making it suitable for large-scale analytics within the AWS Analytics environment.

The dataset features multiple tables, including information on blocks and transactions, messages—reflecting TON’s asynchronous operations composed of multiple message payloads—jetton events that track token transfers, burns, and mints, as well as non-fungible token (NFT) items and transfers detailing ownership and transaction history. Additionally, it includes decentralized exchange trade data such as swap events and pool activities. Together, these tables offer a detailed perspective of the TON blockchain, allowing users to analyze transaction volumes, token flows, NFT activities, and other key blockchain metrics.

Advanced Analysis Of TON Blockchain Data Enabled Through AWS Analytics Services

The TON dataset can be explored using various AWS services such as Amazon Athena, Amazon SageMaker, Amazon QuickSight, and Amazon EMR, enabling users to extract valuable insights from the data. For example, Amazon Athena can be utilized to query the dataset to identify the highest jetton transfer volumes within a specified timeframe, analyze transaction behaviors to uncover trends or irregularities, and monitor NFT sales along with ownership changes throughout the TON network.

Prior to accessing the data on AWS, it is necessary to create the corresponding tables within the AWS Glue Data Catalog. This setup can be accomplished through straightforward AWS CLI commands or by utilizing the chat-with-blockchain-data-with-amazon-bedrock project, which provides CDK-based instructions for table creation and includes a “text to SQL” Amazon Bedrock Agent designed for AI-powered data analysis.

Integrating TON’s dataset into the AWS Public Blockchain Data program represents a notable advancement in improving the availability of TON blockchain information to a global audience. This resource serves researchers investigating blockchain trends, developers working on Web3 applications, and analysts examining DeFi and NFT markets. Users are encouraged to engage with TON’s dataset and employ AWS’s comprehensive analytics tools to discover new insights.

Disclaimer

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About The Author

Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.

More articles
Alisa Davidson
Alisa Davidson

Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.

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