Pump.fun Data

Bitquery provides Pump.fun data as Parquet exports from the Bitquery Data Store, 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.

For the real-time and query-based version of this dataset (GraphQL, WebSocket, gRPC), see the Pump.fun API product page.

Available Pump.fun Topics

For Pump.fun, Bitquery currently provides the following datasets:

• Creation & Migration Events – Pump.fun token creation and migration events

• DEX Trades – Executed trades on Pump.fun

• DEX Pools – Liquidity pool metadata and activity

• OHLCV – Open/High/Low/Close/Volume candles per token

Sample Pump.fun Cloud Dataset

You can explore schemas and validate your tooling using the public Pump.fun sample datasets:

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

Sample Parquet downloads (public S3). The Pumpfun_Sample/ paths are sample paths only.

• Creation & Migration Events – Download

• DEX Trades – Download

• DEX Pools – Download

• OHLCV – Download

Pump.fun Dataset Directory Structure

The Pumpfun_Sample/ folder below holds sample files only.

bitquery-blockchain-dataset/
├── solana/
│   ├── pumpfun_creation_migrations/
│   │   ├── 2026-07-01.parquet
│   │   ├── 2026-07-02.parquet
│   │   └── 2026-07-03.parquet
│   └── dex_trades/
│       └── pumpfun/
│           ├── 390740000_390740049.parquet
│           ├── 390740050_390740099.parquet
│           ├── 390740100_390740149.parquet
│           └── 390740150_390740199.parquet
└── Pumpfun_Sample/
    ├── dex_pools/
    │   ├── 415261250_415261499.parquet
    │   ├── 415261500_415261749.parquet
    │   ├── 415261750_415261999.parquet
    │   └── 415262000_415262249.parquet
    └── ohlcv/
        └── <MintAddress>.parquet

File Naming Conventions

Path and naming differ per topic:

• Creation & Migration Events – solana/pumpfun_creation_migrations/, partitioned by date, <YYYY-MM-DD>.parquet. Each file contains both creations (create / create_v2) and migrations (migrate / migrate_v2):

2026-07-01.parquet

• DEX Trades – solana/dex_trades/pumpfun/, partitioned by slot range, <start_slot>_<end_slot>.parquet:

390740000_390740049.parquet

• DEX Pools – Pumpfun_Sample/dex_pools/ (sample path), partitioned by slot range, <start_slot>_<end_slot>.parquet:

415261250_415261499.parquet

• OHLCV – Pumpfun_Sample/ohlcv/ (sample path), one file per token, named by the token mint address, <MintAddress>.parquet:

2ra5idczuCQhDe1U5D52G8Rms6hzHuHeTqP51fdHpump.parquet

Get Full Access

Buy on the Data Store or email sales@bitquery.io for custom ranges. A Data Store purchase is downloaded from a Requester Pays S3 bucket or a Cloudflare R2 bucket, chosen at checkout. Custom exports can be delivered into your own S3, GCS or R2 bucket, or as a Snowflake or BigQuery share. To trial it first, fill the API form.

Datasets you can buy on the Data Store:

• Pump.fun — bonding-curve trades, token creations, migrations, pools and OHLCV
• PumpSwap — trades on the AMM that Pump.fun tokens migrate to

This listing is not the full catalogue. Other topics, chains and date ranges are available on request from 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/solana/dex_trades/pumpfun/390740000_390740049.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/solana/dex_trades/pumpfun/390740000_390740049.parquet")
print(df.info())
df.head()

Real-Time vs Batch Data Access

Data Store exports are optimized for batch analytics and historical workloads.

If you require low-latency or streaming Pump.fun data, Bitquery also provides:

• Kafka streams

• gRPC (CoreCast) for Solana

• GraphQL subscriptions