During major live sporting events, peak traffic reaches unprecedented levels, and customers expect a flawless in-the-moment experience. The right data infrastructure separates the platforms that win from the ones that fail. This blog uses the FIFA World Cup as an example and explores why successful platforms are building multi-agent systems on a unified data infrastructure to handle seasonal and event-driven traffic spikes.
With YugabyteDB at the core, customer records, vector embeddings, policies, and audit logs live together in a single distributed data layer. There is one source of truth and one consistent answer. This blog shares how to build a fast, explainable copilot on YugabyteDB, combining RAG, CAG, and vLLM in a single distributed Postgres-compatible foundation.
AI models write vanilla PostgreSQL. If your database is distributed, providing the AI model with a YugabyteDB skill file closes the gap and ensures it writes code that works for your application. In this blog, we break down the benchmarking results across 17 model configurations. We conducted 350+ evaluations across Claude 4.5, 4.6, and 4.7, Gemini 3.1 Pro, GPT-5.x, Composer 2, Codex CLI – through Claude Code CLI, Cursor, and Codex. Discover what moved the score, what regressed, and the one structural finding that changes how every team should think about delivering context to an AI coding tool.
Discover a use case for PG advisory lock that protects against write skew and provides a solution for efficient deletes that meet retention requirements. This data modeling keeps the write path predictable and gives practical control of retention cleanup without partition-management overhead.
Cloud migration failures stem largely from misaligned strategies and outdated database architectures. Distributed SQL databases offer a path forward, combining the familiarity of SQL with horizontal scalability, strong consistency, and multi-region resilience. Discover how engineering leaders can turn cloud migrations into a strategic success by modernizing database architecture, planning comprehensively, and investing in skills and automation.
YugabyteDB Anywhere’s embedded Kubernetes operator allows declarative, Kubernetes-native infrastructure-as-code management of multi-cloud topologies leveraging popular service meshes. Discover how the latest YugabyteDB Anywhere features simplify the deployment of YugabyteDB universes across multiple clouds with Kubernetes.
Several recent regional and cloud-wide outages have made multi-cloud solutions more appealing. In this blog, we explore the benefits of these architectures, the considerations to keep in mind, and practical guidance for deploying a multi-cloud YugabyteDB universe.
This blog demonstrates how common distributed SQL system patterns can create write hotspots in distributed architectures, and how ordering, key design, and access paths directly impact scalability. Understanding and addressing the trade-offs is now significantly simpler with YugabyteDB, which enables true lift-and-shift of high-write-throughput applications.
What happens when a relational database design built for e-commerce is pushed to planetary scale? For Shopify, the answer involved years of custom sharding, massive replication overhead, and growing application complexity. Discover how Shopify is navigating the move from large-scale MySQL deployments to YugabyteDB, and what that shift means for engineers building systems at extreme scale.
Discover how to turn scattered documents into a connected knowledge graph using Dify and YugabyteDB. Dify handles AI orchestration while YugabyteDB serves as the unified data backbone, consolidating vectors, relationships, and metadata in one operationally straightforward platform. The end result is a robust system that’s simpler to operate, cost-efficient to scale, and easier to take from prototype to production-ready platform.
