Snowflake Pricing Calculator

Calculate Your
Snowflake Savings

With Qrvey’s Embedded Analytics, You Can Reduce Your Monthly Costs & Snowflake Costs for Analytics Queries

Snowflake Pricing Calculator

Estimating cost savings for a Snowflake warehouse used for ad-hoc queries.
Try our ROI calculator to discover your potential cost savings.

Your Current Snowflake Warehouse

Analytics Warehouse Size:

Cost per Credit: $
Default $3 per credit

Days per month:
Default 22 days per month (weekdays only)

Current Daily Snowflake Usage for All Data Queries

Minutes per day:
Default 6 hours per day

Target Snowflake Usage With Only Real-Time Data Queries

Minutes per day:
If you only used Snowflake for real-time reports, what would usage be then?

Your Savings With Qrvey

Snowflake Savings Over 50% With Qrvey

Qrvey’s embedded analytics for Snowflake can help lower your Snowflake bill and give you a better embedded analytics experience within your SaaS application.

Common Way (Costly)

All data for dashboard usage is backed by Snowflake using a dedicated warehouse for ad-hoc queries.

New Efficient Way

Using Qrvey, single dashboards can combine multiple data sources to minimize the queries to your Snowflake analytics warehouse.

See The Savings: Try Our Snowflake Cost Calculator

Calculate Your Savings

VIDEO

Take a deeper dive on how we help Snowflake customers lower their Snowflake spend.

SNOWFLAKE COST ESTIMATION

Reduce Queries to Snowflake for Embedded Analytics

Qrvey’s embedded analytics for SaaS apps offer the unique ability to combine analytics widgets in a single dashboard using multiple data sources enabling customizable data analysis right by all your users.

Use Snowflake for:

Real-Time Reporting
Use Snowflake for up-to-the-minute real-time reporting needs

Your Data Warehouse
Snowflake stays as your primary source of record for all data

Use Qrvey for:

Near Real-Time Data
Use Qrvey for all data reporting that does not require real-time data

Qrvey as Your Processing Layer
Sync data to Qrvey on a schedule based on reporting needs

HOW IT WORKS

A Hybrid Approach to Embedded Analytics

Real-time data from Snowflake & near real-time data from Qrvey

Embedded Analytics Software

SaaS application users build and customize dashboards using multiple data sources within your SaaS application.

Qrvey Processing Layer

Qrvey’s native processing layer can dynamically query data from multiple sources, routing the query to the appropriate source.

Data Warehouse

Snowflake maintains its role as the primary data warehouse and the source of real-time data, but syncs data to Qrvey to power multi-tenant analytics.

Try It Now: Snowflake Cost Estimator

Calculate Your Savings

Qrvey Provides the Best of Both Worlds

When paired with Snowflake’s serverless infrastructure, organizations can fine-tune the tradeoff between real-time data needs and cost management. The flexibility delivers analytics that are current, comprehensive, and cost-efficient across both real-time dashboards and interactive exploratory analysis.

Seamless Integration

The Qrvey dashboard and visual analytics platform provides a seamless integration with Snowflake’s serverless architecture. By leveraging Qrvey’s flexible connectivity options, organizations can optimize costs while still meeting their real-time and near-real-time analytics needs.

Use Both Live and Near Real-Time

Qrvey offers both live and cached connectivity modes to Snowflake. The live connection delivers true real-time analytics by querying data as it arrives in Snowflake. This ensures users always have access to the freshest data.

Reduce Live Querying Costs

Live connections incur continuous querying costs that may be unnecessary for near-real-time use cases. Qrvey allows SaaS companies to cache data and refresh it on a scheduled basis. The cached data is just seconds or minutes delayed, but slashes the querying costs substantially.

See For Yourself with Our Snowflake Cost Calculator

Calculate Your Savings

FAQs About Snowflake

What are the disadvantages of Snowflake?

Snowflake has high costs if not managed well, limited support for unstructured data, and requires third-party tools for data transformation. Data migration can also be complex.

Why is Snowflake so expensive?

Snowflake’s pay-per-use model can lead to high costs if warehouses aren’t optimized. Compute and storage are billed separately, making expenses unpredictable.

How do you reduce costs in Snowflake?

To reduce Snowflake costs, optimize warehouse sizing, reduce auto-suspend times, limit unnecessary queries, and use resource monitors to track usage. Finally, you can use solutions such as Qrvey.

How much does Qrvey cost?

Qrvey offers flexible pricing tailored to the specific needs of SaaS companies, enterprises, and startups. For detailed pricing information, visit Qrvey’s pricing page.