Startups deploying NoSQL databases and global citizens learning new languages actually share something in common: Both want to remove the limitations on how they access information and express themselves. In launching and growing a platform that enables anyone around the world to connect and speak with native English-speaking tutors on-demand, we’ve had the fortune of helping countless people learn new language skills—and we’ve also learned a great deal ourselves about the best ways to handle the requisite user and application data.
NoSQL, No Problem
Here are four NoSQL database strategy takeaways we learned from recent experience:
Keep Your Data Options Open with Flexible Technology
When a startup is just out of the gate, it isn’t immediately clear what shape the final product may take, or what data it will require.
In our case, the relatively broad scope of our project also defined the need for a database able to function globally with 24/7 availability. The concept for Cambly was born out of its founders’ real experiences traveling to other countries and learning foreign languages through conversations with native speakers. Immersive experiences such as these are critical for gaining and retaining conversational language abilities, and provide learning opportunities that no language course or software can really match. However, these language skills can recede rapidly if a person no longer has access to native speakers to practice with. Seeing this as an issue that technology could address, we began building an application to provide global on-demand access to immersive conversations with native speakers, initially concentrating on English as the largest language market.
As a startup beginning to explore how exactly we’d accomplish the task ahead of us, it was critical that we could store whatever types of data we found to be of value as we quickly iterated the application. This meant utilizing a NoSQL database solution to free ourselves from any schema constraints. We selected MongoDB as a flexible, NoSQL solution with which our technical team had some existing familiarity.
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Startup success is dependent on managing finite internal resources in a way that maximizes the attention that can be devoted to product development and other growth-critical initiatives. This means having the wisdom to rely on managed services where they’re beneficial in saving time and simplifying operations, versus building up internal headcount. For example, we enlisted Heroku to use as our application platform. And, even though our team was experienced in running databases and managing machines on AWS, we still saw the value in keeping production as hands-off as possible and opted for a database-as-a-service (DBaaS) strategy as well.
… And Make Sure It’s the Right Help
It can be tricky, but ensuring that any and all technology service providers a startup works with are a strong fit for its needs is vital to moving quickly. We actually learned this the hard way when it came to our original MongoDB DBaaS. For us, reliable 24/7 availability and insights into database performance were essential requirements. Unfortunately, our initial provider presented us with two challenges to meeting these requirements in a short time frame: Its tools became unable to provide us with visibility into our database, and it announced a required platform migration that could not be completed without downtime. Naturally, these changes led us to seek a better-fitting option. Soon after, we partnered with mLab in large part due to rolling node replacement capabilities for migrations and 24/7 uptime, as well as support and tooling that could help our team quickly optimize MongoDB instances.
Get the Database Tools You Need to Succeed
From reliable data backups to performance insights and beyond, the right toolset can make or break a burgeoning company’s success. Just as language skills must be constantly attended to, your database requires intelligent upkeep and backups to ensure it delivers a satisfactory user experience and remains available in case of disaster. This is one lesson which—very fortunately—we were able to absorb without hardship. We had an incident in which our team accidentally deleted a trove of valuable data. But, with data backups in place, our DBaaS was able to help us restore that data quickly—and without us stressing over it as we would have otherwise. At the same time, the DBaaS tools allow us to recognize and address database issues while improving indexing and performance.
