Nansen Query Documentation
  • Introduction
  • Overview
    • 📍Getting Started
    • 📍Benefits of Curation
  • Data
    • 🗃️Data Sources
    • 🗃️Data Catalog
      • 🗃️Raw Events
      • 🗃️Aggregates
        • Entity Stats
        • Address Stats
        • Token Usage Stats
        • Transaction Stats
        • Address & Their Relationships
      • 🗃️Dex Trades
        • 🗃️Dex Trader P&L
        • 🗃️Dex Trader Use Cases
        • 🗃️Advanced Topics
        • 🗃️Trader P&L FAQ
      • 🗃️Decoded Contracts
      • 🗃️NFTs
      • 🗃️Governance
      • 🗃️Solana
        • 🗃️Solana Aggregates
    • 🗃️Repeated / Nested Fields
    • 🗃️Adding New Projects
    • 🗃️Data Marketplace
  • Web App
    • 🖥️Overview
    • 🖥️Getting Started: Web App
    • 🖥️My Queries
    • 🖥️Query Editor
    • 🖥️Visualizations
    • 🖥️Dashboards
    • 🖥️Dashboard Editor
    • 🖥️Refresh Schedules
    • ⚙️Custom Query APIs
      • ⚙️API Keys
      • ⚙️Execute A Query
      • ⚙️Get Query Results
  • Database Access
    • 📂Database Overview
    • 📂Getting Started: Database
    • 📂Sample Queries
      • 📂Wallet Examples
      • 📂Token Examples
      • 📂Trader P&L
      • 📂Project Examples
      • 📂Solana Queries
      • 📂Blockchain Examples
    • 📂Sample Python Code
      • 📂Wallet Examples
      • 📂Token Examples
    • 📂Cost Optimization
    • 📂Database FAQs
  • Other
    • ⁉️General FAQs
    • 🏷️Wallet Labels
Powered by GitBook
On this page
  1. Database Access

Cost Optimization

How to save money when querying using BigQuery.

PreviousToken ExamplesNextDatabase FAQs

Last updated 2 years ago

Sometimes it can be expensive to query data from BigQuery, here are some tips on how to optimize costs.

1) Rarely use SELECT * Big query costs are based on the amount of data processed, selecting all columns results in every column being processed, which can be expensive

2) LIMIT 100 DOES NOT save costs! Big query costs are based on the amount of data process, not the size of the result. LIMIT doesn't reduce the amount of row scanning.

3) Apply filters as early and as often as you can Filters reduce the amount of data that has to be processed, directly reducing the cost

Source:

📂
https://cloud.google.com/blog/products/data-analytics/cost-optimization-best-practices-for-bigquery