Architecting GenAI and
RAG Apps with YugabyteDB

Flexible data infrastructure for AI-powered applications

Hello RAG!Azure AI Search Explore Vector Search

Want to rapidly deploy GenAI and RAG apps at scale?

Most new applications include an AI component. Legacy apps may require retooling for Retrieval-Augmented Generation (RAG) functionality and to meet evolving business requirements.

Your data makes AI apps accurate and relevant

GenAI alone isn’t useful. A RAG architecture enhances LLMs with your enterprise data.

YugabyteDB provides advanced vector indexing capabilities.

Ultra-resilience and scalability are critical

AI apps require high availability, ultra-resilience, and painless scale.

YugabyteDB’s distributed architecture delivers this and supports over 100M vectors.

Rapid iteration, high flexibility

Rapidly evolving standards, including MCP, A2A, and ACP, require flexible architectures.

Flexible Postgres-compatible YugabyteDB meets changing industry standards.

Advanced Vector Indexing and Distributed SQL Capabilities

YugabyteDB combines the power of the pgvector PostgreSQL extension with an inherently distributed architecture. This future-proofed foundation helps you build AI-powered, data-driven applications—including RAG and Agentic AI—that demand high-performance vector search.

YugabyteDB’s unique approach to vector indexing addresses the limitations of single-node PostgreSQL systems when dealing with large-scale vector datasets.

Unparalleled Horizontal Scalability for AI Apps

Confidently grow your business with an AI-ready data layer that easily and quickly scales queries, storage, and connections.

Easily manage 100s of millions of vectors with ultra-low-latency vector query response times
Respond to unexpected demand with simple, automatic, rapid horizontal scalability
Deliver high availability with active-active replication

Distributed Indexing and Seamless Similarity Search

YugabyteDB enables vector indexes to be distributed naturally across the database cluster. This accelerates indexing and vector queries across massive datasets. YugabyteDB’s sophisticated data retrieval and analysis allow you to use vector search to find similar documents that meet specific criteria.

Achieve even distribution of vector indexes across clusters
Perform vector similarity searches directly using SQL
Filter, join, and aggregate vector and SQL queries in a single, standard SQL statement

Flexible Architecture

Build your AI-powered applications with confidence.

YugabyteDB’s extensible indexing framework supports the seamless integration of state-of-the-art vector indexing libraries and algorithms. This ensures that your apps can quickly capitalize on new advancements and optimizations.

Extensible indexing framework designed to support evolving vector indexing libraries and algorithms
YugabyteDB’s future-ready design provides flexibility and customization for new libraries
Run scalable, resilient, and feature-rich vector searches, with the power and familiarity of PostgreSQL

Choosing the Right Database for GenAI Apps

There are critical design choices you should consider when selecting a database, specifically when choosing between a dedicated vector database and a distributed SQL, multi-modal database like YugabyteDB.

Feature	Standalone Vector Database	YugabyteDB with Vector Search
Vector Search
Horizontal Scalability	May offer
Ultra Resilient
Consistency	Varies	Strong Consistency
Full SQL Support	Limited or none
Data Model	Vector, maybe Document	Multi-Model: Vector, Relational, Document, Key-Value
Traditional SQL + Vectors
Familiar PostgreSQL
ACID Compliant
Only One Database Required
Low Operational Complexity
Low TCO (Small, POC Projects)
Low TCO (Full Production, at Scale)
Row-Level Security
Low/Zero Learning Curve
High Queries/Second
Query Flexibility	Vector	SQL + Vector
Geo-Located Data	May offer
Deploy in Hybrid/Multi-Cloud	May offer
Growing Postgres AI Ecosystem
Geo-Distributed Architecture
Open Source	May offer

Architecting GenAI and RAG Apps with YugabyteDB

Want to rapidly deploy GenAI and RAG apps at scale?

Advanced Vector Indexing and Distributed SQL Capabilities

Choosing the Right Database for GenAI Apps

Learn More

Architecting GenAI and
RAG Apps with YugabyteDB