Category: Best Practices and Tutorials
Couchbase Partners with Arize AI to Enable Trustworthy, Production-Ready AI Agent Applications
Couchbase partners with Arize AI to bring observability to production-ready AI agent apps. Learn to build, monitor, optimize Agentic RAG solutions at scale.
Data Migration: Strategy, Best Practices & Tools
Learn about types of data migration, best practices, tools, and pitfalls to avoid to create an effective data migration strategy.
Ensuring High Availability with Automatic Failover for App Services
Boost app reliability with Python-based automatic failover. Monitor server health and switch WebSocket connections seamlessly to keep users connected.
Self-Hosted AI Chatbots with Docker and Couchbase Capella
Build a private, self-hosted AI chatbot using Docker Model Runner & Couchbase Capella. Fast, flexible, and fully under your control—no external APIs needed.
MongoDB to Couchbase – Migrations Tips
Moving from MongoDB to Couchbase? This guide covers everything you need to know— benefits, migration strategies, query conversion & post-migration tuning.
Build Highly Scalable AI/ML Applications With Couchbase and PySpark
Couchbase Spark Connector now supports PySpark! Build fast, scalable data pipelines and ML apps with Couchbase and Apache Spark in Python.
Build Your First Open Source AI Agent with Couchbase
Build an open-source AI agent with Python, JavaScript, and Couchbase. Automate tasks and deploy your own AI assistant—completely free!
Extending RAG capabilities to Excel with Couchbase, LLamaIndex, and Amazon Bedrock
Extend Retrieval Augmented Generation (RAG) capabilities to Excel using Couchbase, LlamaIndex, and Amazon Bedrock. Make spreadsheets searchable.
Chat With Your Git History, Thanks to RAG and Couchbase Shell
Turn your Git history into a chat-ready knowledge base using RAG and Couchbase Shell.
A Guide to LLM Embeddings
Learn how LLMs generate and use embeddings to enhance natural language processing, improve search relevance, and enable AI-driven applications.
Data Normalization vs. Denormalization Comparison
Learn the primary differences between data normalization vs. denormalization, along with their benefits, challenges, and use cases.
What is Conversational Analytics? Plus Examples and Tools
Learn how conversational analytics helps improve customer interactions and drives business growth. Also, find use cases and tools that will help.
Top Posts
- Data Analysis Methods: Qualitative vs. Quantitative Techniques
- What are Embedding Models? An Overview
- Data Modeling Explained: Conceptual, Physical, Logical
- What Is Data Analysis? Types, Methods, and Tools for Research
- Application Development Life Cycle (Phases and Management Models)
- High Availability Architecture: Requirements & Best Practice...
- A Guide to Vector Search
- What are Vector Embeddings?
- Filtered ANN Search With Composite Vector Indexes
