From MySQL Bottlenecks to Firebolt Power: 28X Faster Analytics at Lower Cost

We built a BI platform to give subscription-based businesses the insights they need to grow. Sublytics lets our clients track everything from customer metrics to campaign ROI, handling millions of transactions seamlessly. As our client base and data needs grew, we hit a major challenge: keeping analytics fast and scalable without costs getting out of control.

The Problem: Hitting MySQL’s Limits

Our initial setup was a straightforward LAMP stack. MySQL handled things well enough early on, but larger clients with more complex analytics needs began pushing our infrastructure to the edge. Reports that had previously run smoothly started slowing down and, in some cases, timed out entirely. To deal with this, we tried adding read replicas and caching, but it was basically putting a band-aid on the problem. We needed something that could handle large datasets and complex queries without compromising response times.

Evaluating Solutions

We checked out several options: Snowflake, Redshift, and other data warehousing solutions. Firebolt, however, stood out for its low-latency capabilities and scalable design. Firebolt could handle large query loads with minimal response times, without forcing us to scale up endlessly. After some initial testing, we felt confident that Firebolt would keep our performance high while simplifying our infrastructure.

Firebolt Implementation

The impact of moving to Firebolt was immediate. Complex reports that took minutes to run on MySQL now returned in sub-seconds. For instance, one query that used to take 4 seconds in MySQL now runs in just 0.142 seconds with Firebolt—a 96% reduction in time, making it roughly 28 times faster. This leap in performance enables our clients to view metrics like revenue, ad spend, and customer engagement across hundreds of millions of rows almost instantly.

Another major improvement was how Firebolt improved our data refresh capabilities. Before, we could only refresh data three times a day, which left clients with data that was hours old. Now, Firebolt enables us to refresh data every 30 minutes. If you’re spending hundreds of thousands of dollars a day on marketing, you need your data as close to real-time as possible. This improvement has kept analytics timely for clients who make high-stakes campaign decisions based on current results.

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Lower Costs, More Speed

Scaling MySQL to support this level of analytics was expensive, requiring multiple large read replicas and additional ETL processes to manage the growing workload. Firebolt’s decoupled storage and compute architecture allowed us to scale resources independently, reducing costs while maintaining top performance:

• ETL Cost Reduction: We eliminated AWS Glue from our stack, saving $4,000 a month. Firebolt’s ingestion process lets us move data efficiently without heavy transformation costs.
• Reduced Infrastructure: By cutting our MySQL replicas in half, we saved an additional $1,500 monthly. With fewer resources needed to manage our analytics workload, our overall infrastructure costs decreased.
• Optimized Partitioning: Firebolt’s partitioning and data ingestion capabilities allowed us to remove much of our old infrastructure. This simplification reduced both our maintenance load and complexity.

Since moving to Firebolt, we’ve scaled to handle 50,000 client queries daily without slowdowns. Clients who used to wait seconds—or face timeouts—now get results so fast that it’s spoiled them. If a report takes more than four seconds, we hear about it. Under MySQL, that same report might have timed out completely.

The Result: Analytics That Scale

Firebolt has freed us from spending countless hours troubleshooting performance issues and patching infrastructure. As our client base grows, Firebolt's ability to handle hundreds of millions of rows ensures our analytics remain fast and scalable, regardless of future demands.

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