![]() ![]() In our example, we pick a birth time of 18:23 UTC.ĭaily_amt AS (SELECT cast(date AS date) AS date, sum(input_value) AS amt FROM btc. Every block has a time stamp, and we can identify the closest block for any given time in the last 13 years. New Ethereum blocks are created every 12-14 seconds. ![]() On average, a new Bitcoin block is created every ten minutes. This template sets up AWS Glue Data Catalog, Amazon Athena Workgroup with a S3 bucket for the query results, and AWS Lambda functions to keep partitions up-to-date:Įxample 1) Tell me the “birth block” for my childīitcoin has been around since January 2009 and Ethereum since July 2015. In addition, we provide Jupyter notebooks here for Amazon SageMaker Studio that demonstrate how to perform cross-chain analytics and how to combine blockchain data with market trends for fundamental on-chain analytics.īefore you can run these examples, you need to deploy the following AWS CloudFormation template. Parquet files in Amazon S3 can be directly queried in Amazon Athena or Amazon Redshift. On AWS, you can take advantage of multiple tools to access and analyze these datasets. Currently, we provide the historical block and transaction data for both chains and some additional tables for Ethereum that are most commonly used for queries. The schema of the Parquet files is documented for each table and field here. The following folder structure is currently provided for Bitcoin and Ethereum blockchain data in the public Amazon S3 bucket.īitcoin: s3://aws-public-blockchain/v1.0/btc/ The blockchain data is then transformed into multiple tables as compressed Parquet files partitioned by date to allow efficient access for most common analytics queries. You can also see which AWS services can be utilized to access this data from the public Amazon S3 bucket.Īfter taking an initial download of the full blockchain from the first block in 2009 for Bitcoin and in 2015 for Ethereum, an on-chain listener continuously delivers new data to the public Amazon S3 bucket that provides the open datasets. The following architecture diagram shows which AWS services are used to extract the data from the public blockchains and how it is delivered to Amazon Simple Storage Service (Amazon S3). You can load these files partitioned by date into your AWS environment and use AWS services like Amazon Athena or Amazon Redshift on top of this data to query it efficiently with SQL. Solution overviewįor these datasets we deployed an architecture to extract, transform, and load blockchain data into a column-oriented storage format that allows for easy access and expedited analysis. In addition, these datasets normalize data into tabular data structures and you can instantly access years worth of data across chains in a format that can be easily analyzed and queried by data scientists and other analytics professionals. The public blockchain datasets allow you to have immediate access to this data without operating dedicated full nodes for the different blockchains and without building complicated ingestion pipelines. The growing NFT market also has a wealth of metadata, ripe for exploration and analysis.Įach distributed ledger is designed in a unique way and uses different technology stacks and consensus algorithms. A growing number of distributed applications embed metadata in other blockchains to validate ownership of assets beyond cryptocurrency. Additionally, these blockchains are often used to host metadata that doesn’t impact or affect the transfer of tokens on that particular network. This includes public keys and addresses where tokens were exchanged, transaction volume and times, and metadata that highlights mining difficulty, network hash rates, available supply. However, querying these distributed ledgers directly is time consuming, inefficient, and unsuited for analytics.īlocks on each chain contain information about transactions across the network. TBs of data sit on these blockchains as users transact tokens, share information, and deploy smart contracts. Although these blockchains are public, accessing and analyzing data across multiple chains continues to be a challenge for Web3 builders. With the increase of Web3 activity around the world, more and more data is hosted on public blockchains. Today, AWS launches accessible Bitcoin and Ethereum blockchain datasets for public use. You can find the open-source project on GitHub here and the public blockchain datasets here. These datasets are still experimental and are not recommended for production workloads. In this post, we share an open-source solution for running cross-chain analytics on public blockchain data along with public datasets for Bitcoin and Ethereum available through AWS Open Data. ![]()
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