An open-source distributed event-streaming platform like Apache Kafka supports data fabric by handling real-time data streaming across various systems.
Pruning graph databases makes LLMs faster and more efficient by removing unnecessary info and improving recommendations while saving power and resources.
Big O Notation is probably going to be the first thing you hear about when learning about data structures and algorithms. Let's make it easy to understand.
Resolve the "Database cannot be opened" issue in SQL Server caused by MDF file corruption with methods like backup restoration, DBCC CHECKDB, or repair tools.
Optimize performance, minimize costs, and ensure scalability in Azure Cosmos DB with practices like selecting the right partition key and tuning queries.
Skip if-else statements by using design patterns, polymorphism, and functional strategies for cleaner, more adaptable, and significantly more testable code architectures.
In this blog, I will discuss key software development trends for 2025, from AI-powered tools to ethical AI, low-code platforms, and cloud-native advancements.
Ensuring database reliability can be difficult. Our goal is to speed up development and minimize rollbacks. Achieving efficient processes requires database observability.
A DMZ cluster in Kubernetes secures public services from internal workloads, enhancing scalability, reducing attack surface, and ensuring controlled access.
Big data isn’t dead; it’s just going incremental. But bad things happen when uncontrolled changes collide with incremental jobs. Reacting to changes is a losing strategy.
Online issues can be highly complex, requiring the capture of key information for a clear understanding. Through logical reasoning, the root cause was pinpointed.
This article guides you through setting up a GraphQL server, defining schemas, and integrating with React, highlighting benefits and potential challenges.
The three data storage options and their pros and cons: the legacy data warehouse, the more recent data lake, and contemporary data lakehouse architectures.
You will learn how to run PostgreSQL in a Docker container with a portable, isolated, and resource-efficient database setup that is easy to manage and scalable.
Learn about Apache Iceberg catalogs, their types, configurations, and the best-fit solutions for managing metadata and large datasets in different environments.