Build an AI-Ready Data Foundation With Confidence
December 4, 2025
AI is raising the bar of what your data infrastructure needs to deliver. It’s no longer just about storing and retrieving information, modern applications need real-time context, global reach, continuous availability, and the elasticity to scale instantly.
AI doesn’t change the importance of data, it simply exposes weaknesses faster and at a much larger scale. If you’re building or modernizing AI-driven systems, the database you choose matters more than ever.
Download “Evaluating YugabyteDB: A Comprehensive Assessment of a Distributed SQL Database for AI-Driven Workloads,” written by Sanjeev Mohan, Principal, SanjMo and Former Gartner Research VP, Data & Analytics to discover what to look for in a next-generation data platform and how YugabyteDB meets those demands.
This is an essential guide for architects, engineering leaders, and data teams evaluating distributed SQL for the AI era.
The Database Evaluation Playbook
Discover a structured framework for evaluating modern databases, including:
How to Match Use Cases to the Right Data Model
YugabyteDB’s multi-API support for relational, document, multi-modal workloads, streaming integration, and vector embeddings gives developers the flexibility they need to deliver AI-powered systems. Learn how the database handles OLTP and analytical patterns, plus how pgvector enables RAG, semantic search, and high-speed similarity lookups.
A Deep Dive Into Distributed Architecture
YugabyteDB’s shared-nothing design, Raft consensus, and global replication come together to deliver strong consistency and fault tolerance. The assessment explains multi-region active-active writes, Kubernetes-native operations, and the cloud-native foundations behind fully-managed YugabyteDB Aeon.
Delivering Availability and Resilience at Any Scale
Discover deployment models, multi-region failover, PITR, and disaster recovery strategies. The white paper details how organizations can maintain continuous uptime, and illustrates the layers of availability and operational safeguards.
Elastic Scalability Designed for AI Demands
YugabyteDB scales both compute and storage independently, supports automated horizontal growth, and manages high-volume workloads without downtime. The assessment highlights serverless auto-scaling within YugabyteDB Aeon and details how intelligent load distribution ensures predictable performance.
Performance Across OLTP, Analytics, and Vector Workloads
Discover indexing strategies, distributed query execution, compression techniques, and benchmark results, including YugabyteDB’s ability to handle billion-vector datasets. The performance section reveals what to expect in production.
Improving Developer and Data Team Productivity
YugabyteDB’s PostgreSQL compatibility, multi-API support, natural-language integrations fit into modern DevOps, IaC, and AI frameworks. From SQL to CQL to vector search to GraphQL, you can work with data in a way that suits you best.
Security, Governance, and Observability Built for Enterprise AI
YugabyteDB supports fine-grained access control, encryption, audit logging, regulatory compliance, distributed tracing, and metrics dashboards. Learn how to implement guardrails for AI agents interacting with structured data.
Operational Automation and Smooth Migrations
The assessment outlines Kubernetes-powered automation, self-healing capabilities, and zero-downtime maintenance. It explains how open source migration tool YugabyteDB Voyager streamlines migrations from Oracle, PostgreSQL, and MySQL, with step-by-step workflows.
Vendor and Ecosystem Considerations
With insights into open-source licensing, pricing transparency, community health, support tiers, and YugabyteDB’s technical pedigree, learn how to evaluate long-term viability and platform fit.
Conclusion
Whether you’re building AI-powered personalization, global transactions, high-speed vector search, or real-time analytics, your data platform must be ready for distributed, intelligent workloads by default.
YugabyteDB combines the familiarity of PostgreSQL with the resilience, scalability, and cloud-native architecture required by modern AI applications. It provides strong consistency, global performance, and continuous availability.
This new white paper provides CTOs, architects, and developers with a clear, structured framework to evaluate whether their data infrastructure is ready for modern, intelligent workloads. It also details how YugabyteDB meets architecture, scale, performance, governance, operations, and ecosystem maturity expectations.
If you’re exploring distributed SQL, preparing for cloud modernization, or designing AI-driven applications, this white paper will help you make informed decisions with confidence.
