BSC Data - BNB Chain

Bitquery provides BSC (BNB Chain) blockchain data dumps in Parquet format, designed for large-scale analytics, historical backfills, and data lake integrations. These datasets can be hosted directly in your own cloud storage (for example, AWS S3) and queried using engines like Snowflake, BigQuery, Athena, Spark, etc.

Available BSC Topics

For BSC (BNB Chain), Bitquery currently provides the following datasets:

• Blocks – Block-level metadata
• Transactions – Full transaction-level data
• Transfers – Native BNB and token transfers (BEP-20)
• Balance Updates – Account balance changes per block
• DEX Trades – Executed trades on BSC DEXs (PancakeSwap, etc.)
• DEX Pools – Decentralized exchange pool metadata
• Smart Contract Calls – Function calls and contract interactions
• Events – BSC event logs and emissions
• Miner Rewards – Block rewards and transaction fees

Sample BSC Cloud Dataset

You can explore schemas and validate your tooling using the public BSC sample datasets:

GitHub reference (schemas & examples)
https://github.com/bitquery/blockchain-cloud-data-dump-sample/tree/main/bsc

Example Parquet file (public S3)

https://bitquery-blockchain-dataset.s3.us-east-1.amazonaws.com/bsc/balance_updates/<block_range>.parquet

BSC Dataset Directory Structure

bitquery-blockchain-dataset/
└── bsc/
    ├── balance_updates/
    │   ├── <start_block>_<end_block>.parquet
    │   ├── <start_block>_<end_block>.parquet
    │   └── ...
    ├── blocks/
    │   ├── <start_block>_<end_block>.parquet
    │   ├── <start_block>_<end_block>.parquet
    │   └── ...
    ├── calls/
    │   ├── <start_block>_<end_block>.parquet
    │   └── ...
    ├── dex_pools/
    │   ├── <start_block>_<end_block>.parquet
    │   └── ...
    ├── dex_trades/
    │   ├── <start_block>_<end_block>.parquet
    │   └── ...
    ├── events/
    │   ├── <start_block>_<end_block>.parquet
    │   └── ...
    ├── miner_rewards/
    │   ├── <start_block>_<end_block>.parquet
    │   └── ...
    ├── transactions/
    │   ├── <start_block>_<end_block>.parquet
    │   └── ...
    └── transfers/
        ├── <start_block>_<end_block>.parquet
        └── ...

Block Range Naming Convention

Each Parquet file name follows this format:

<start_block>_<end_block>.parquet

Example:

77611000_77611049.parquet

Get Full Access

The full dataset is delivered into your own cloud storage (S3, GCS) or warehouse share (Snowflake, BigQuery). To buy or trial it, fill the API form or contact sales@bitquery.io.

Reading Files with DuckDB

No key, no client library — point DuckDB at the public sample directly:

SELECT *
FROM read_parquet('https://bitquery-blockchain-dataset.s3.us-east-1.amazonaws.com/bsc/dex_trades/77611000_77611049.parquet')
LIMIT 10;

Reading Files in Python

import pandas as pd

df = pd.read_parquet("https://bitquery-blockchain-dataset.s3.us-east-1.amazonaws.com/bsc/transfers/77611000_77611049.parquet")
print(df.info())
df.head()

Real-Time vs Batch Data Access

Cloud data dumps are optimized for batch analytics and historical workloads.

If you require low-latency or streaming BSC data, Bitquery also provides:

• Kafka streams
• GraphQL subscriptions