Systems | Development | Analytics | API | Testing

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Java String Methods: A Guide With Examples

Strings are important concepts in programming and are data types that allow storage of character sequences. String methods are built-in functions that are called on a string to either get information or manipulate data. In Java, strings are treated as immutable data, therefore their values cannot be changed. To work with strings and perform operations on them, you need to understand string methods in Java and how they work.

Connect with Confluent Q4 Update: New Program Entrants and SAP Datasphere Hydration

The Connect with Confluent (CwC) Technology Partner Program consistently expands the reach of Confluent’s data streaming platform across an ever-growing landscape of enterprise data systems. In this blog, you’ll meet the latest program entrants who have built fully managed integrations with Confluent and discover new ways to leverage real-time data across your business.

Load testing tools: comparison of Loadero and LoadNinja

"Load, load testing, load test this, load test that, Loadero, LoadNinja, load, load, load... ugh, what should I choose?!'' - we can only imagine what the experience of choosing a load testing tool is like. The Loadero team has decided to ease the burden of choosing between testing tools by writing a comparison review about Loadero and LoadNinja. By the way, if you’re considering testRTC as an option too, we have published a similar article before, where we compared Loadero and testRTC.

Top 3 Data and Analytics Trends to Prepare for in 2025

2025 is poised to be another year of significant advancements in business intelligence (BI) and analytics. Building on the momentum of 2024, which saw a surge in self-service BI adoption, our attention turns to newer, sophisticated artificial intelligence (AI) solutions. As the data landscape evolves, it’s important to keep agile and adapt to emerging technologies to stay competitive and maximize the value of your analytics investments.

Elevating Productivity: Cloudera Data Engineering Brings External IDE Connectivity to Apache Spark

As advanced analytics and AI continue to drive enterprise strategy, leaders are tasked with building flexible, resilient data pipelines that accelerate trusted insights. AI pioneer Andrew Ng recently underscored that robust data engineering is foundational to the success of data-centric AI—a strategy that prioritizes data quality over model complexity.

Pay-As-You-Live: The Future of Life and Health Insurance Unveiled

The insurance industry is experiencing a profound shift, moving away from traditional models toward more personalized, data-driven solutions. The “Pay-As-You-Live (PAYL)” model leads this change, a groundbreaking life and health insurance approach that adjusts premiums based on each individual’s lifestyle choices and behaviors. Rather than relying on general statistics and broad risk categories, Pay-As-You-Live customizes coverage to reflect the unique health habits of each policyholder.

Cut Unnecessary Tests

Is your test suite running as efficiently as it could? @Titus Fortner explains why the number of tests isn't always the problem—it's the value they bring. Deleting tests that constantly fail and don’t provide useful data can significantly reduce your total execution time. Here's what to consider when refining your test suite: Ready to make your test suite more efficient? Watch this episode of Test Case Scenario to learn more.

Data integrity in Ably Pub/Sub

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.