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निर्माण शुरू करेंएसओसी 2 टाइप II प्रमाणित · आईएसओ 27001
The easiest way to backfill blockchain data
Backfill templates are prebuilt with Streams to get you the historical data you need as quick as possible.
Select the datasets you want to backfill with clarity and control. Know exactly what data you'll receive and how it will be delivered.
Streams, the engine behind backfills, offers guaranteed data delivery to Snowflake, Amazon S3, Webhooks, and more.
Once you have your historical data, continue your stream to get the freshest possible blockchain data available.
Quickly backfill historical Base block and transactions data for comprehensive blockchain analysis and insights.
Quickly backfill historical Base block, transactions and receipts data for comprehensive blockchain analysis and insights.
Quickly backfill historical Base receipts data for comprehensive blockchain analysis and insights.
Quickly backfill historical Base traces data (debug_trace) for comprehensive blockchain analysis and insights.
Quickly backfill historical Base traces data (trace_block) for comprehensive blockchain analysis and insights.
Quickly backfill historical Base blocks, transactions, receipts and traces data (debug_trace) for comprehensive blockchain analysis and insights.
Quickly backfill historical Base blocks, transactions, receipts and traces data (trace_block) for comprehensive blockchain analysis and insights.
Quickly backfill historical Base (ERC20/721/1155) transfers for comprehensive blockchain analysis and insights.
Quickly backfill Base all Uniswap V2/V3 Swaps transfers for comprehensive blockchain analysis and insights.
Want to learn more about how to further level up your ETL pipelines? Check out our blog on how Streams and Functions work together to create industry-leading blockchain ETL solutions.
If you need a tailored pricing plan that aligns with your specific backfilling requirements, we're here to help. Our team will work with you to develop a customized solution that best fits your project's demands.
See for yourself in seconds.