
High Availability vs. Fault Tolerance: Key Differences
High availability and fault tolerance are both strategies for maintaining system operationality, but they differ in approach and complexity. High availability focuses on minimizing downtime through rapid recovery, while fault tolerance ensures uninterrupted operation even in the event of failures....

Streams by Datanexions & Couchbase: A Revolution for Real-Time Data Integration
Effectively exploiting data in real time is a challenge that companies face; Whether it’s about optimizing the customer experience, improving decision-making, or ensuring transaction security, managing data flows is a strategic issue. The combination of Couchbase and Streams by Datanexions...

Polaris: AI-Powered Conversational Data Intelligence for the Enterprise Through a Multi-Agent Architecture
In today’s fast-paced environment, the ability to swiftly access, understand, and act upon data is no longer a luxury , it’s a necessity. However, many organizations find that while they are rich in data, deriving timely, actionable insights remains a significant...

Rethinking Node Drains: A Webhook Based Approach to Graceful Pod Removal
Why and how we built an admission controller to make node drains safer when running stateful applications in Kubernetes. Running stateful applications in Kubernetes is increasingly common and these are often managed using custom resources and operators. However, the dynamic...

3 EF Core Integrations That Work with Couchbase
Couchbase’s new EF Core provider opens the door to some powerful .NET integrations: even ones traditionally tied to relational databases. This post walks through how Identity, GraphQL, and OData all work with Couchbase. In this post, I’ll walk through three...

Introducing the Fully Managed Couchbase Connector for Confluent Cloud
Building real-time applications often requires connecting operational databases like Couchbase with data streaming platforms such as Confluent. But managing these integrations can be complex, requiring teams to deploy connectors, configure networking, manage schemas, and monitor performance. These challenges slow development...

How Modern Data Platforms Are Transforming Financial Services
The financial services industry stands at a critical crossroads. Traditional institutions that once dominated through branch networks and institutional trust now face fierce competition from digital-native challengers who promise instant everything—instant payments, instant approvals, instant insights. Meanwhile, client expectations have...

Designing a Serverless Data Archiving Pipeline from Couchbase to Cloud Storage
In modern data-driven applications, retaining historical documents is essential for compliance, auditing, and cost optimization. However, keeping all data indefinitely in your primary operational database is often unsustainable and expensive. In this blog post, I’ll walk you through building a...

Why You Only Need Couchbase When Building Your Agents
Agents are intelligent systems powered by large language models (LLMs) that can autonomously perform tasks, make decisions, and interact with users or other systems. Unlike traditional software, agents can understand natural language inputs, determine what actions to take, and use...

Couchbase Integration with Hyperledger Fabric: A Technical Deep Dive
What is Couchbase? Couchbase is a distributed NoSQL document database that provides a flexible, high-performance, and scalable data management solution. It combines the best features of document databases with key-value stores, making it well-suited for modern application development. Key features...

Vector Database vs. Graph Database: Differences & Similarities
What is a vector database? A vector database is a type of database designed to store, index, and search high-dimensional vector representations of data, typically generated by machine learning models. These vectors, also known as embeddings, capture the semantic meaning...

Couchbase and K2view Partner on Synthetic Data for Building AI Applications
Artificial Intelligence is only as effective as the data it learns from. For many organizations, the challenge isn’t access to data, but access to safe, representative, and adaptable data. That’s where synthetic data comes in. By mimicking the structure and...