Visualize Ethereum ERC20 Token Data Using Amazon Managed Blockchain Query and Amazon QuickSight

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Analyzing Ethereum-based ERC20 token activity is essential for businesses issuing stablecoins or managing digital assets. Understanding key metrics—such as top holders, daily active users, transaction volume, and DeFi platform usage—can drive strategic decisions and improve transparency. With Amazon Managed Blockchain (AMB) Query and Amazon QuickSight, organizations can extract, process, and visualize blockchain data efficiently—without the complexity of maintaining infrastructure.

This guide walks through a serverless solution that leverages AWS services to create real-time, insightful dashboards for ERC20 tokens like PayPal’s PYUSD. Whether you're tracking token distribution or monitoring user engagement, this architecture delivers accurate, cost-effective analytics.

👉 Discover how to unlock blockchain insights with powerful analytics tools.

How AMB Query Powers ERC20 Token Analytics

Amazon Managed Blockchain Query simplifies access to Ethereum blockchain data by offering standardized APIs that retrieve finalized, on-chain information. This eliminates the need for running custom nodes or complex indexing systems.

Continuously Updated Finalized Data

To monitor real-time token behavior—like daily transfers or active wallets—AMB Query provides two critical APIs:

For instance, Paxos could use these APIs to track every movement of its PYUSD stablecoin. By analyzing transaction hashes, businesses can identify patterns such as frequent transfers to DeFi protocols, enabling deeper insight into user behavior.

Historical Token Holder Analysis

Understanding long-term trends requires historical data. The ListTokenBalances API returns a complete snapshot of all token holders at any given time. This allows you to answer questions like:

Because AMB Query serves historically indexed data via REST APIs, there's no need to build custom ETL pipelines or maintain expensive databases.

Cost-Efficient Blockchain Data Access

Traditional blockchain analytics often involve high infrastructure costs due to node operation and data indexing. AMB Query removes this burden with a pay-as-you-go model, charging only for API calls made. Pricing is predictable and scales with usage, making it ideal for startups and enterprises alike.

You avoid the "undifferentiated heavy lifting" of blockchain data management while gaining immediate access to reliable, finalized data.

Solution Architecture Overview

This solution integrates multiple AWS services into a seamless pipeline:

  1. AMB Query fetches raw token data.
  2. AWS Glue runs Python scripts to extract and store data in Amazon S3.
  3. Amazon S3 acts as durable storage for structured CSV files.
  4. Amazon Athena enables SQL-based querying of S3-stored data.
  5. Amazon QuickSight visualizes insights through interactive dashboards.

The result? A fully automated system that updates token metrics hourly or daily, depending on your needs.

👉 See how automated data pipelines simplify blockchain analysis.

Step-by-Step Implementation

Prerequisites

Ensure you have an AWS account with proper IAM permissions configured. Specifically, grant access to AMB Query, AWS Glue, S3, Athena, and QuickSight.

Create an S3 Bucket

All extracted data will be stored in Amazon S3. Create a new bucket using the AWS Console or CLI. Once created, AWS Glue jobs will automatically write data to designated folders within this bucket.

Follow AWS documentation to set up your first bucket.

Extract Data with AMB Query

Use the interactive Query Editor in the AMB Query console to test API calls. For example:

This returns all transactions involving the PYUSD token during that period. You can then drill down into individual transactions using ListTransactionEvents.

Automate Data Extraction with AWS Glue

Two Glue jobs handle data collection:

1. token-transfers – Track Real-Time Activity

This job captures every transfer event for continuous monitoring of:

Setup Steps:

  1. In AWS Glue Console, create a new Python shell script.
  2. Name it token-transfers.
  3. Paste code from token-transfers.py.

  4. Set job parameters:

    • --token: 0x6c3ea9036406852006290770BEdFcAbA0e23A0e8
    • --s3_bucket_name: your-bucket-name
  5. Schedule hourly execution to keep data fresh.

2. token-snapshot – Capture Holder Distribution

This job runs daily to snapshot all token balances.

Setup Steps:

  1. Create another Glue job named token-snapshot.
  2. Use code from token-snapshot.py.
  3. Set the same parameters as above.
  4. Schedule daily execution at midnight UTC.

Both jobs export CSV files to S3 under paths like:

Query Data with Amazon Athena

Athena allows SQL querying of S3 data without managing servers.

Run these DDL statements to create external tables:

CREATE EXTERNAL TABLE events(
 contractaddress string,
 eventtype string,
 from string,
 to string,
 value string,
 transactionhash string,
 transactiontimestamp string
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES ('escapeChar'='\\', 'quoteChar'='\"', 'separatorChar'=',')
STORED AS TEXTFILE
LOCATION 's3://BUCKET-NAME/TOKEN-ADDRESS/events'
TBLPROPERTIES ('skip.header.line.count'='1');
CREATE EXTERNAL TABLE token_snapshot(
 address string,
 balance string
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES ('escapeChar'='\\', 'quoteChar'='\"', 'separatorChar'=',')
STORED AS TEXTFILE
LOCATION 's3://BUCKET-NAME/TOKEN-ADDRESS/snapshot'
TBLPROPERTIES ('skip.header.line.count'='1');

Now you can run queries like:

SELECT COUNT(*) AS daily_active_users
FROM events
WHERE DATE(transactiontimestamp) = CURRENT_DATE;

Build Dashboards in Amazon QuickSight

QuickSight transforms raw data into actionable visuals.

Import Data

  1. Open QuickSight Console → New analysis → New dataset.
  2. Choose Athena as source.
  3. Connect to AwsDataCatalog and select your tables (events, token_snapshot).
  4. Choose Directly query your data for real-time updates.

Create Visualizations

Add time-series graphs for:

Dashboards can be shared across teams or embedded in internal portals.

Frequently Asked Questions (FAQ)

Q: Can I analyze other ERC20 tokens besides PYUSD?
A: Yes! Simply update the token contract address in the Glue job parameters to analyze any ERC20 token on Ethereum.

Q: Is this solution compatible with other blockchains?
A: Currently, AMB Query supports Ethereum mainnet and select testnets. Multi-chain support is expanding.

Q: How often should I run the snapshot job?
A: Daily is recommended for balance tracking. For high-frequency tokens, consider more frequent runs with incremental updates.

Q: Can I export dashboard data?
A: Yes, QuickSight allows exporting visuals as PDFs or CSVs for reporting and compliance purposes.

Q: Are there alternatives to AWS Glue for ETL?
A: While Lambda or Step Functions can work, Glue offers serverless scalability and native integration with S3 and Athena.

Q: How secure is the data stored in S3?
A: S3 supports encryption at rest (SSE-S3, SSE-KMS), versioning, and fine-grained IAM policies to ensure data protection.

Conclusion

Visualizing ERC20 token data doesn’t require building blockchain infrastructure from scratch. By combining Amazon Managed Blockchain Query, AWS Glue, Athena, and QuickSight, businesses gain a powerful, scalable analytics pipeline that’s both cost-effective and easy to maintain.

From tracking daily active users to mapping ownership concentration, this solution empowers issuers—from fintech firms to Web3 startups—to make informed decisions based on real on-chain activity.

👉 Start turning blockchain data into business intelligence today.