Stream Blockchain Data into Google BigQuery


Blockchain data can significantly enhance data analytics in BigQuery. Google's BigQuery is renowned for its robust data warehousing and analytics capabilities, yet it may not fully tap into the potential of blockchain data natively, without proper integration. Riverflow provides a seamless solution to connect blockchain with BigQuery, enabling you to unlock its full potential. This guide outlines how Riverflow can be used to integrate blockchain data into BigQuery.

Why BigQuery with Blockchain Data?

Incorporating blockchain data into BigQuery will give you:

  • Comprehensive Analytics: Combine blockchain data with traditional datasets in BigQuery for a more holistic view of your analytics landscape.

  • Blockchain-Driven Insights: Understand how blockchain transactions and smart contract interactions influence broader data trends.

  • Enhanced Data Querying: Leverage BigQuery's powerful querying capabilities to explore and analyze blockchain data efficiently.

Getting Started with Riverflow and BigQuery

Here’s how to integrate Riverflow with BigQuery:

  1. Set Up Riverflow Account: Create your account on

  2. Event Selection for BigQuery: Decide which blockchain events you wish to import into BigQuery and apply the necessary filters.

  3. Choose BigQuery as Destination: In Riverflow, go to the "Destination" section, select 'Choose Destination' > 'Google BigQuery'.

Streaming Blockchain Data into BigQuery

To successfully stream data into BigQuery:

  1. Configure BigQuery Destination:

    • BigQuery Secret Account Key: Enter your secret account key to identify the right account where Riverflow data should be streamed (learn more on how to get your SAK here)

    • Region: The region where your data should be host

    • Dataset: The name of the dataset where blockchain data should be sent (you need to have created this dataset in BigQuery before)

    • Table: The name of the table to feed with blockchain data (you need to have created this table in BigQuery before)

  2. Customize Data Schema: Adapt the blockchain data schema to fit your BigQuery table structure in the customization section. You want to make sure that the names of the variables sent to you table are matching.

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