Systems | Development | Analytics | API | Testing

BigQuery ML contribution analysis models, now GA, automate insight generation and output key change drivers from multidimensional data.

Choosing the right relational database management system (RDBMS) is a critical decision for any organization. Two of the most widely adopted options are Microsoft SQL Server and MySQL. Both platforms have evolved rapidly, introducing new features and enhancements that reflect the changing needs of modern data-driven applications. This updated 2025 comparison explores their latest capabilities, performance, security, and suitability for different use cases.

In today’s API-driven world, strong API design is key to building reliable and scalable services. Without structure or standardization, the design phase can quickly spiral into chaos. Common problems like misaligned teams, tightly coupled systems, code duplication, and inconsistent standards begin to snowball. This causes delays, poor customer experiences, and in some cases, long-term technical debt that becomes a serious business risk.

E2E Testing is a method to test a software from the consumer’s perspective. It involves simulating real scenarios, including user interfaces, backend testing. The purpose of E2E testing is to validate the application’s overall behavior, including its functionality, reliability, performance, and security. E2E Testing helps in identifying issues when one or more components interact with each other. It is usually done after integration testing, which tests individual component.

In today’s high-speed world of software delivery, performance engineering can’t afford to be a bottleneck. Teams are shifting left, moving fast, and integrating feedback loops earlier and more often, but performance feedback still too often lags. If your performance testing still hinges on last-mile validations or project-based assessments, you’re not alone. Many teams are struggling with how to evolve their practices from siloed testing to scalable, integrated performance engineering.

We’re excited to announce Ably LiveObjects, launched with a radical vision: to enable any application to work with live, shared data that synchronizes instantly for users everywhere. Shared access to live data is no longer a nice-to-have - it’s becoming a foundational building block of every realtime digital experience.

Agentic AI has the potential to revolutionize workplace processes in nearly every sector by improving business decision-making, workflow efficiency and customer interactions and experiences. While interest in agentic AI is widespread, the motivation to use it differs by industry. Cloudera surveyed 1,484 enterprise IT leaders across 14 countries to better understand their approach to agentic AI in 2025, including how specific industries plan to implement the technology.

The need for impeccable mobile applications is unequivocal. Users want intuitive interfaces, smooth functionality, and uniform performance across various devices and operating systems. Development teams have a considerable difficulty in satisfying these requirements while expediting release cycles. Conventional mobile app testing services, although fundamental, often fail to keep pace with the velocity and complexity of contemporary application development.

Smarter AI starts long before the model is trained. It begins with the quality of the data you feed it. Data that reflects real-world nuance, cultural context, and human behavior is what sets strong systems apart.

When it comes to error monitoring in mobile apps, iOS and Android take distinct approaches due to their unique architectures and tools. Here’s a quick breakdown of the key differences.