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“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
Choosing between HubSpot API ETL and Snowflake Data Share depends on your data volume, technical resources, and performance requirements. Both approaches have distinct trade-offs in speed, cost, and complexity.
Here’s how each method performs and why there’s a third option that might work better for your team.
Compare all three HubSpot data access methods using Coefficient
CoefficientHubSpotTraditional HubSpot API ETL requires custom development and hits rate limits of 100-1000 requests per 10 seconds. Snowflake Data Share offers near real-time access but needs SQL expertise and variable compute costs.provides a third option with directintegration that handles up to 50,000+ rows without infrastructure costs.
Performance-wise, Coefficient excels for ad-hoc analysis, rapid prototyping, and business user self-service scenarios. You get optimized data retrieval with built-in scheduling and incremental refresh capabilities, all through a zero-code interface.
How to make it work
Step 1. Connect directly to HubSpot without API rate limit concerns.
Use Coefficient’s optimized connection to pull HubSpot data efficiently. The system handles batching and pagination automatically, eliminating the performance bottlenecks of traditional API ETL approaches.
Step 2. Configure focused datasets with advanced filtering.
Apply up to 25 filter conditions to work with specific data subsets. This approach loads data quickly while maintaining real-time connectivity, giving you the performance benefits without massive dataset overhead.
Step 3. Set up automated refreshes for consistent performance.
Schedule regular data updates that run in the background. Unlike Snowflake compute costs or API rate limit management, these refreshes operate on predictable subscription pricing regardless of data volume.
Step 4. Use incremental updates for ongoing efficiency.
Enable “Append New Data” to add only new records without full dataset refreshes. This approach maintains performance as your data grows while providing the change tracking capabilities you’d get from more complex ETL solutions.
Choose the right approach for your data needs
Start with CoefficientFor teams processing moderate data volumes with regular reporting needs, Coefficient typically provides the best performance-to-complexity ratio.to get immediate HubSpot data access without the infrastructure overhead of traditional ETL or data warehouse solutions.
