Blockchain data in your warehouse. No pipeline to run.
Bitquery datashares deliver petabyte-scale, decoded on-chain history straight into Snowflake, BigQuery, S3 or Azure — refreshed daily, queryable with your own SQL. No nodes, no ETL, no infrastructure to maintain.
Land the data where you already work.
A datashare arrives natively in your cloud — no copy job to babysit. Point your existing SQL, BI and ML tools at it and the tables stay fresh on their own.
Snowflake
A native Snowflake share — query Bitquery tables in your account, no copy, no pipeline.
BigQuery
A shared BigQuery dataset that lands in your project and refreshes on schedule.
Amazon S3
Partitioned Parquet dropped to your bucket — point Athena, Spark or DuckDB at it.
Azure ADLS
Delivered to Azure Data Lake for Synapse, Databricks and Fabric workloads.
Decoded tables, ready to query.
Every dataset is a typed, partitioned table — the same schema across chains. Select what you need and join it to your own data with plain SQL.
SELECT block_time, dex, pair, side, price_usd, amount_usd FROM bitquery.dex_trades WHERE chain = "ethereum" AND block_date >= "2026-06-01" ORDER BY block_time desc limit 100
Building your own blockchain pipeline is the slow path.
Nodes, decoders, schedulers and a warehouse loader — just to get queryable data. A datashare is the table, already in your account, already fresh.
From raw share to production, fast.
Query the share directly, or join it to your own tables — it's just SQL.
Warehouse-native analytics
Run dashboards, cohorts and attribution over decoded trades, transfers and balances without moving a byte out of your warehouse.
Read the docs →Train models & feed agents
Use clean, structured history as features for ML, or expose it to LLM agents — the same data backs our MCP server.
Read the docs →Audit & custody datasets
Give auditors and risk teams a complete, queryable record of on-chain activity for reconciliation and reporting.
Read the docs →What teams say about our data
"We did a thorough search of the market for the best onchain data. Bitquery came out on top — and now powers all live prices across Nansen. We don't think of them as a vendor. They're a partner."
Bitquery does the hard work of parsing blockchain transaction data into a usable form so that we don't have to. We use their interface to diagnose issues with complex transactions and their analytics as a starting point for our own.
They proved they had the technology to deliver sophisticated data solutions. We extended our support through the Binance X fellowship — building an open-source library of visualization widgets on their blockchain data.
The complex raw data is available at different levels of detail and from different viewpoints — whether we need simple aggregated transfers or parameters for failed contract calls. The support is responsive, friendly and quick.
Partnering with Bitquery has been highly cost-effective — leveraging their established infrastructure rather than building our own let us rapidly expand our blockchain support and reach a much broader segment of on-chain users.
Bitquery's products are very intuitive and easy to use. We currently use their products to obtain DEX-related trading and liquidity information, which saves us the manpower and tedious technical details required to develop our own system. Their excellent technical team deserves special praise; they provide near-24/7 support and resolve issues quickly. I greatly appreciate their products and work ethic.
Bitquery provides the infrastructure we rely on every day. Fast, reliable, and comprehensive across the chains that matter to our business.
Start free. Scale when you ship.
Query every blockchain on every plan — no chain is paywalled. Move to commercial when you need volume, SLAs and bulk datashares.
- All blockchains, all plans
- 10 requests / minute
- 2 streams for testing
- GraphQL IDE access
- Scalable calls, no throttling
- SQL, Cloud, Kafka & more
- 24/7 engineering access
- Dedicated onboarding & SLA
- Snowflake, BigQuery, S3, Azure
- No setup or infrastructure
- Structured for AI agents & MCP
- Audit data for custodians
Datashares, answered.
How do Bitquery datashares work?
Which warehouses and clouds do you support?
How often is the data refreshed?
Which datasets are available?
Can I use the data to train models or feed AI agents?
What does pricing look like?
Put on-chain data in your warehouse.
Petabyte history, decoded, refreshed daily — shared natively into Snowflake, BigQuery, S3 or Azure. No pipeline to build.