SingleStore

Why does running a distributed database( SingleStore ) on Kubernetes feel like a solved problem until your first production upgrade? That's exactly where most teams hit a wall. As a Solutions Engineer, I spend a lot of time with teams post-deployment. And the gap is almost never the initial setup. It's the operational muscle: rolling upgrades without downtime, recovering from node failures gracefully, knowing which metrics actually matter vs. the noise. Stateful databases on K8s demand a different mindset than stateless workloads. The Day-0 decisions - storage class, topology, shard keys design quietly define your Day-2 experience. This article breaks down what production operations actually look like. Not just how to deploy, but how to operate with confidence once you're live.

Coming from a DBA background, I’ve worked on many databases over the years, and one thing became very clear to me: Great performance always starts with strong fundamentals especially datatypes and performant functions. Today, many database wants to call itself an “AI” or “Vector” database. But the real test begins when you start building actual AI/vector workloads at scale. That’s when you discover whether the database was truly engineered for AI complexity — or whether the vendor starts suggesting endless workarounds and “Jugad” 😄 This is where SingleStore genuinely stands out. Its powerful combination of native vector datatypes and rich vector functions creates a solid foundation for modern AI applications. It feels less like “adding AI support” and more like a database actually designed to handle AI/vector workloads efficiently. For anyone working deeply in databases, that foundation matters a lot. #singlestore #database #oracle #mysql #AI #vectordb

Most Product Led Growth content is written for product managers. I wrote this one for engineers. After leading the PLG and Growth team at SingleStore, here's what I've learned. https://lnkd.in/eTiWfJe5

My experience with LOT Polish Airlines today highlights a critical gap that many legacy enterprises still face: the distance between their customer-facing front end and their real-time data reality. The Chain Reaction of a Data Failure: Concurrency Failure: A payment system timeout prevented a simple outbound flight change. This could be a high-concurrency issue where the database can't keep pace with transactional demand. System would not me change my flight and I was on hold for a long time behind 11 people on the phone. The "Single Source of Truth" Gap: Because the system didn't reconcile my new flight I had booked in real-time, it triggered an automated cancellation of my original return flight. Fragmented Context: The AI-driven WhatsApp agent had no visibility into the payment error and reverted to its default language (Polish). Even the live agent, after 30 minutes, lacked the cross-silo data to resolve the issue, eventually defaulting to a manual contact center. This isn't a "customer service" problem. It’s a data architecture problem. I am not sharing this to complain, every business is on a journey to modernize but to point out that "Agentic AI" and "Customer Centricity" are impossible without a high-performance Context and Speed Layer. How SingleStore bridges this gap: At SingleStore, we help global leaders like Delta eliminate these friction points by unifying transactions and analytics in a single, real-time engine: High-Concurrency Payments: We enable payment systems to process massive transaction volumes without timeouts, ensuring the "handshake" between the customer and the ledger is instantaneous. Real-Time Data Sync: We eliminate silos so that every touchpoint—from the gate agent to the mobile app—operates on a single, unified source of truth. No more "ghost" cancellations. The Foundation for Agentic AI: AI agents are only as smart as the data they can access. We provide the real-time vector and historical context required for AI to actually solve problems, rather than just route them to a human. LOT Polish Airlines, your team is clearly working hard to improve the experience, but there is a clear disconnect with your data infrastrucure. I’d love to discuss how we’ve helped other major carriers fix these exact issues and build a truly real-time enterprise. Who is the best person on your digital or architecture team to start that conversation? SingleStore #DataArchitecture #RealTimeData #Airlines #DigitalTransformation #SingleStore #EnterpriseAI #CustomerExperience