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:
35000000_35000049.parquet
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