Systems | Development | Analytics | API | Testing

ClickHouse is a high-performance, columnar database designed for analytics and big data applications. One of ClickHouse's standout features is its ability to perform filtering directly on compressed data, enabling faster results compared to traditional relational databases. While working with ClickHouse, you will often encounter the WHERE and PREWHERE clauses, both of which are used to filter data. But what is the difference between WHERE and PREWHERE, and when should you use one over the other?

“Quality is more important than quantity. One home run is much better than two doubles.” – Steve Jobs In the world of software testing, this quote couldn’t be more relevant. If you’re a manual tester, you know the pressure to deliver high-quality results, often within tight deadlines and limited resources. Yet, with today’s fast-paced software development cycles, meeting these demands through manual testing alone is increasingly challenging.

As data analysts navigate the evolving landscape of data integration, finding the right platform to streamline workflows and optimize processes is critical. Among the many tools available, Workato and Integrate.io have emerged as leading solutions for connecting applications, automating workflows, and managing complex data pipelines.

In today’s data-driven world, the ability to efficiently integrate, transform, and analyze data can significantly impact business outcomes. As organizations collect data from an ever-expanding number of sources, ETL (Extract, Transform, Load) platforms have become indispensable tools for data analysts. Choosing the right ETL solution is a critical decision, as it influences data workflow efficiency, security, compliance, and ultimately, the quality of insights derived.

Scalability testing ensures your software application can handle increased loads as user demand grows. This makes it crucial for businesses looking to support growth and maintain high availability.

The global software testing market is projected to reach $109.5 billion by 2027, with a significant portion dedicated to automated testing.

Today’s fast-paced development environments require new approaches to testing. Enter continuous performance testing. Unlike traditional performance testing, automated continuous performance testing is part of every build, monitoring the application continuously under increased load. With continuous performance tests, organizations with lots of users can expect to improve the customer experience, prevent major outages, and find and resolve issues faster.

‍ In our previous article, The Key to Unlocking QSR Growth, we discussed the guiding principles that lay a strong foundation for success in the Quick Service Restaurant (QSR) industry. We highlighted the importance of data analytics for improved decision-making, automation, and scalable growth.

When you publish a message to Ably Pub/Sub, you can be confident that the message will be delivered to subscribing clients, wherever they are in the world. Ably is fast: we have a 99th percentile transmit latency of <50ms from any of our 635 global PoPs, that receive at least 1% of our global traffic. But being fast isn’t enough; Ably is also dependable and scalable. Ably doesn’t sacrifice data integrity for speed or scale; it’s fast and safe.

Welcome to the latest edition of the Katalon Product Roundup, featuring updates from October 2024. This release includes significant updates across Katalon Studio, TrueTest, and TestCloud, each designed to improve your testing workflows and boost overall efficiency. Read on to discover the latest features!