PayJoy Cuts Snowflake Data Warehousing Costs by 21% with Keebo
Challenges
- 37% increase in usage and queries drastically increased Snowflake costs
- Manual optimization was reducing data engineers’ availability for data analysis
- Poor use of data engineering resources
Results
PayJoy’s analytics team and data engineers now have the time they need to fully support their internal business partners because Keebo automated all of their data warehouse optimizations and slashed Snowflake costs by 21%.
“I’m confident Keebo will deliver every possible cost saving, which frees me to support our internal business partners,” says Trish Pham, Head of Analytics, PayJoy. “We never felt good about spending too little time on the manual optimizations and letting costs get out of control, or spending so much time on optimization that we neglected our internal business partners.”
Significant Savings Within 48 Hours
As PayJoy’s rapid growth drove a 37% increase in Snowflake usage, from 1.6 million to 2 million queries, manually optimizing queries, pipelines and data usage simply wasn’t an option. PayJoy turned to Keebo for platform-independent, automated warehouse optimization and within 48 hours, data warehousing costs had already dropped significantly.
Keebo Customer Story
About PayJoy
PayJoy provides mobile e-financing for “underbanked” consumers. The company launched in 2015 and has tripled its revenue since 2020. PayJoy has more than 500 employees in 7 countries.
Industry
Financial Services
Headquarters
San Francisco, California, United States
Data Cloud Platform
Snowflake
Keebo Product
Keebo Warehouse Optimization
Key Benefits
- 21% drop in data warehousing costs despite query increase, from 1.6 to 2 million
- 48 hours to achieve cost savings
- 100s of additional hours available for data analysis and internal customer support
Keebo Customer Story
About PayJoy
PayJoy provides mobile e-financing for “underbanked” consumers. The company launched in 2015 and has tripled its revenue since 2020. PayJoy has more than 500 employees in 7 countries.
Industry
Financial Services
Headquarters
San Francisco, California, United States
Data Cloud Platform
Snowflake
Keebo Product
Keebo Warehouse Optimization
Key Benefits
- 21% drop in data warehousing costs despite query increase, from 1.6 to 2 million
- 48 hours to achieve cost savings
- 100s of additional hours available for data analysis and internal customer support
Challenges
- 37% increase in usage and queries drastically increased Snowflake costs
- Manual optimization was reducing data engineers’ availability for data analysis
- Poor use of data engineering resources
Results
PayJoy’s analytics team and data engineers now have the time they need to fully support their internal business partners because Keebo automated all of their data warehouse optimizations and slashed Snowflake costs by 21%.
“I’m confident Keebo will deliver every possible cost saving, which frees me to support our internal business partners,” says Trish Pham, Head of Analytics, PayJoy. “We never felt good about spending too little time on the manual optimizations and letting costs get out of control, or spending so much time on optimization that we neglected our internal business partners.”
Significant Savings Within 48 Hours
As PayJoy’s rapid growth drove a 37% increase in Snowflake usage, from 1.6 million to 2 million queries, manually optimizing queries, pipelines and data usage simply wasn’t an option. PayJoy turned to Keebo for platform-independent, automated warehouse optimization and within 48 hours, data warehousing costs had already dropped significantly.
“The biggest thing I love about Keebo is how easy and hands-off it is to use and the fact it takes care of the things that I don’t want to think about or deal with. Keebo requires no work on my end, and even if I loved manual optimization, I couldn’t possibly achieve what Keebo achieves automatically.”
Trish Pham, Head of Analytics
PayJoy
Reallocate Valuable Engineering Time
To deliver significant and ongoing cost reductions, Keebo analyzes the queries and the underlying data automatically to learn usage patterns, without requiring the users or database administrators to provide hints or custom configurations. It also detects data updates and reacts to workload changes automatically.
Keebo frees up hundreds of hours of valuable engineering time that would otherwise be spent on tedious performance optimization tasks. PayJoy onboarded their warehouses in less than 30 minutes without requiring any changes to their existing applications. As soon as Keebo connected to their data warehouse, it automatically learned a set of “smart models” by analyzing the workload, including warehouse settings, database schema, data distribution, and query patterns. This Data Learning process considers multiple factors before deciding which optimizations will be the most effective. Keebo’s fully automated process determines and applies optimizations without user assistance or manual intervention.
Keebo continuously monitors the cost and performance of the incoming queries and adjusts its optimizations accordingly to account for any workload changes. Optimizations that are no longer beneficial are automatically retired, and new ones are created to accommodate the additional load.
“With Keebo, I log in for a few minutes every few weeks just to see what Keebo is saving us. Before Keebo, I spent hours on manual optimizations every week. Keebo really freed up my time which is a great bonus on top of the cloud warehousing bill reductions.”
When discussing new solutions, Trish’s manager always asks, “Is it helpful? Do you really need it?” And for both Trish and her manager, “Keebo was just a no-brainer decision.”
Ready to Achieve Similar Results?
