Can you share an overview of Humblytics?

Certainly. Humblytics is a primary analytics tool for Webflow, co-founded by Amir and me, who previously ran a full-service B2C agency. Our challenges were twofold: integrating effective analytics for performance tracking and identifying areas for improvement.

Google Analytics was the traditional choice, but it posed difficulties due to overwhelming data and complex setup via Google Tag Manager. With the rise of no-code tools like Webflow, analytics remained a pain point. To address this, we created Humblytics, offering effortless setup by authenticating SSL through Webflow for automatic script installation. This verifies website ownership and tracks events like form submissions and clicks instantly.

How did you discover Timescale?

I had some experience with basic SQL and MongoDB setups, but dealing with something at this scale was new to me. Amir and I realized we didn’t have the budget to hire data engineers or experts in the field.

Then, I recalled my time at Interspace, a company specializing in indoor intelligence. They tracked millions, even billions, of events with just a small team of 10, so I reached out to them for advice. They recommended Timescale for their database needs.

After Googling Timescale, I was shocked by how incredibly user-friendly and cost-effective it is to get started.

What were the key requirements for you when choosing a database?

Our top priority was ensuring platform scalability during popularity surges and client traffic spikes. We wanted a managed service to avoid manual AWS maintenance, while ensuring high reliability.

Our users demand Google Analytics-level reliability, even during rapid growth, expecting uninterrupted performance and unlimited storage. Disruptions or system downtime for paying users could lead not only to data loss, but also erode trust in our platform.

How did you get your first tests going?

The initial test involved writing insert statements, followed by creating a basic proof of concept. We then funneled real web analytics data into the database and assessed service utilization for future vertical scaling.

Unlike many other managed tools that add unnecessary complexity, Timescale made the process smooth and intuitive, particularly for those familiar with SQL. Our testing began in April, and we launched publicly in May or June.

What were the aha moments for you that Timescale would solve your problem?

Signing up with Timescale provided immediate access to a connection string containing the necessary detail—username, password, and database name. It was straightforward, requiring no extra steps. Creating my first table, a hypertable, was another smooth experience with no unexpected surprises or steep learning curves. The dashboard, like the Explorer for table navigation and metrics/logs just made sense. It was all very intuitive.

The 30-day free trial allowed us to thoroughly test the platform to ensure it met our needs. The managed aspect of Timescale saved us from opening an AWS account solely for database setup.

What are the biggest benefits you’ve received from Timescale?

Timescale provides us with scaling insurance, so we don’t have to worry about performance issues, storage limitations, or data loss negatively impacting our users, which has been crucial for maintaining growth and user trust. Features like read scaling, high availability, and data tiering, addressed any scalability concerns and helped us make the decision to build Humblytics on Timescale.

What does your upstream stack look like? Were there any features that stood out to make your workflow easier?

Our current setup isn't too complex—we run a Node.js server on Heroku, which passes through Cloudflare to reach our Node.js server. This server then sends data to Timescale.

Two notable features that greatly benefited our workflow were compression and aggregates. Compression proved valuable in reducing storage costs, while aggregates streamlined data management by summarizing it. Instead of storing multiple instances of the same event, like button clicks, aggregates facilitate quicker querying for these counts and streamline our data-handling process.