In the technology landscape, startups navigate pivotal decisions shaping their future.
For startups not venturing into SDK creation, Firebase alone might serve adequately. It's undeniably robust, but with growth, we experienced a surge in costs. This led us to explore complementing it with other platforms for a well-rounded backend.Firestore undoubtedly transformed our data management with its real-time capabilities. However, certain nuances in its querying process became evident.
Transitioning Firebase actions to the back end and implementing caching became our strategy to manage expenses without compromising the user experience.Our U.S.-centric SDK had to cater to an international clientele. This posed challenges, like when we tried to incorporate test phone numbers for our international team. Firebase's authentication, while comprehensive, wasn't always seamless for a worldwide user base.
Firebase is a powerful tool, but ensuring it syncs with your existing tech stack may require tweaks and refinements.Firebase's scalability was enticing. However, our experiences—combined with forward-thinking—highlighted some limitations. We encountered rising costs with certain Firestore calculations. These were optimized either by shifting to PostgreSQL, caching data in the backend or employing Redis.
Imagine a scenario where a singular microservice handles real-time client communication via web sockets while other services broadcast updates or events. Kafka, with its distributed stream-processing prowess, emerged as an ideal candidate for this role, potentially synergizing well with Firestore's real-time features.
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