Java Virtual Threads Performance Benchmark: Platform vs Virtual Threads

Remember a time when we all agreed that blocking JDBC couldn't possibly scale? Java 25 just changed the game. Between Virtual Threads and the latest JVM optimizations, the "simple" blocking pattern has been vindicated. We can finally have both i.e. our application scalability and our readable code, too. I just posted another update to my series on Non-Blocking vs. Blocking JDBC. After many years of tracking this, the answer seems to be Java 25. Check it out: https://lnkd.in/daW7aWrM #Java #Programming #Backend #TechTrends

Day 7 of #100DaysOfCode — Java is getting interesting ☕ Today I explored the Java Collections Framework. Before this, I was using arrays for everything. But arrays have one limitation — fixed size. 👉 What if we need to add more data later? That’s where Collections come in. 🔹 Key Learnings: ArrayList grows dynamically — no size worries Easy operations: add(), remove(), get(), size() More flexible than arrays 🔹 Iterator (Game changer) A clean way to loop through collections: hasNext() → checks next element next() → returns next element remove() → safely removes element 🔹 Concept that clicked today: Iterable → Collection → List → ArrayList This small hierarchy made everything much clearer. ⚡ Array vs ArrayList Array → fixed size ArrayList → dynamic size Array → stores primitives ArrayList → stores objects Still exploring: Set, Map, Queue next 🔥 Consistency is the only plan. Showing up every day 💪 If you’re also learning Java or working with Collections — let’s connect 🤝 #Java #Collections #ArrayList #100DaysOfCode #JavaDeveloper #LearningInPublic

🚀 Sealed Classes + Records in Java — Clean Code or Just Hype? Java 17+ introduced Sealed Classes and Records, and honestly, together they solve two very real problems we’ve all faced: 👉 Uncontrolled inheritance 👉 Boilerplate-heavy data classes 🔒 Sealed Classes — Finally, Control Over Who Can Extend public sealed interface Payment permits CardPayment, UpiPayment {} This ensures: ✔️ Only defined types can implement your interface ✔️ No unexpected extensions ✔️ Safer and more predictable domain models 📦 Records — Say Goodbye to Boilerplate public record CardPayment(String cardNumber) implements Payment {} public record UpiPayment(String upiId) implements Payment {} ✔️ Immutable by default ✔️ No getters / constructors / equals / hashCode needed ✔️ Perfect for DTOs, APIs, event-driven systems ⚡ Together — This is Where It Gets Interesting Sealed → controlled hierarchy Record → immutable data switch(payment) { case CardPayment c -> System.out.println(c.cardNumber()); case UpiPayment u -> System.out.println(u.upiId()); } 💡 The compiler knows all possible types → fewer bugs, cleaner logic 🤔 Now I’m curious… Are you using sealed classes in your projects? Where exactly? Have records replaced your DTOs, or are you still relying on Lombok/classes? Any real-world challenges with Spring Boot, JPA, or serialization? 👇 Would love to hear how you’re using these features in production #Java #Java17 #SealedClasses #Records #CleanCode #JavaDeveloper #BackendDevelopment #SoftwareEngineering #Microservices #APIDesign #CodingBestPractices #TechDiscussion

Most Java developers have used ThreadLocal to pass context — user IDs, request IDs, tenant info — across method calls. It works fine with a few hundred threads. But with virtual threads in Java 21, "fine" becomes a memory problem fast. With 1 million virtual threads, you get 1 million ThreadLocalMap instances — each holding mutable, heap-allocated state that GC has to clean up. And because ThreadLocal is mutable and global, silent overwrites like this are a real risk in large systems: userContext.set(userA); // ... deep somewhere ... userContext.set(userB); // overrides without warning Java 21 introduces ScopedValue — the right tool for virtual threads: ScopedValue.where(USER, userA).run(() -> {   // USER is safely available here, immutably }); It's immutable, scoped to an execution block, requires no per-thread storage, and cleans itself up automatically. No more silent overrides. No memory bloat. No manual remove() calls. In short: ThreadLocal was designed for few, long-lived threads. ScopedValue is designed for millions of short-lived virtual threads. If you're building high-concurrency APIs with Spring Boot + virtual threads and still using ThreadLocal for request context — this switch can meaningfully reduce your memory footprint and make your code safer. Are you already using ScopedValue in production, or still on ThreadLocal? Would love to hear what's holding teams back. #Java #Java21 #VirtualThreads #ProjectLoom #BackendEngineering #SpringBoot #SoftwareEngineering

📖 New Post: Java Memory Model Demystified: Stack vs. Heap Where do your variables live? We explain the Stack, the Heap, and the Garbage Collector in simple terms. #java #jvm #memorymanagement

A few fundamental Java concepts continue to have a significant impact on system design, performance, and reliability — especially in backend applications operating at scale. Here are three that are often used daily, but not always fully understood: 🔵 HashMap Internals At a high level, HashMap provides O(1) average time complexity, but that performance depends heavily on how hashing and collisions are managed internally. Bucket indexing is driven by hashCode() Collisions are handled via chaining, and in Java 8+, transformed into balanced trees under high contention Resizing and rehashing can introduce performance overhead if not considered carefully 👉 In high-throughput systems, poor key design or uneven hash distribution can quickly degrade performance. 🔵 equals() and hashCode() Contract These two methods directly influence the correctness of hash-based collections. hashCode() determines where the object is stored equals() determines how objects are matched within that location 👉 Any inconsistency between them can lead to subtle data retrieval issues that are difficult to debug in production environments. 🔵 String Immutability String immutability is a deliberate design choice in Java that enables: Safe usage in multi-threaded environments Efficient memory utilization through the String Pool Predictable behavior in security-sensitive operations 👉 For scenarios involving frequent modifications, relying on immutable Strings can introduce unnecessary overhead — making alternatives like StringBuilder more appropriate. 🧠 Engineering Perspective These are not just language features — they influence: Data structure efficiency Memory management Concurrency behavior Overall system scalability A deeper understanding of these fundamentals helps in making better design decisions, especially when building systems that need to perform reliably under load. #Java #BackendEngineering #SystemDesign #SoftwareArchitecture #Performance #Engineering

🔥 Java Records — Cleaner code, but with important trade-offs I used to write a lot of boilerplate in Java just to represent simple data: Fields… getters… equals()… hashCode()… toString() 😅 Then I started using Records—and things became much cleaner. 👉 Records are designed for one purpose: Representing immutable data in a concise way. What makes them powerful: 🔹 Built-in immutability (fields are final) 🔹 No boilerplate for getters or utility methods 🔹 Compact and highly readable 🔹 Perfect for DTOs and API responses But here’s what many people overlook 👇 ⚠️ Important limitations of Records: 🔸 Cannot extend other classes (they already extend java.lang.Record) 🔸 All fields must be defined in the canonical constructor header 🔸 Not suitable for entities with complex behavior or inheritance 🔸 Limited flexibility compared to traditional classes So while Records reduce a lot of noise, they are not a universal replacement. 👉 They work best when your class is truly just data, not behavior. 💡 My takeaway: Good developers don’t just adopt new features—they understand where not to use them. ❓ Question for you: Where do you prefer using Records—only for DTOs, or have you explored broader use cases? #Java #AdvancedJava #JavaRecords #CleanCode #BackendDevelopment #SoftwareEngineering

Java Collections seem straightforward… until edge cases start showing up in real-world code. Here are a few more collection behaviors worth knowing 👇 • Null handling in collections HashMap allows one null key, Hashtable allows none — small difference, big impact. • contains() vs containsKey() Using the wrong one in Map can lead to incorrect checks. • Size vs Capacity (ArrayList) size() is actual elements, capacity is internal storage — confusion can lead to performance issues. • remove() ambiguity in List remove(1) removes by index, not value — use remove(Integer.valueOf(1)) for value. • equals() & hashCode() importance Custom objects in HashSet/HashMap need proper overrides or duplicates may appear. • Iteration order assumptions HashMap order is unpredictable — don’t rely on it unless using LinkedHashMap or TreeMap. • Immutable collections (List.of) They throw UnsupportedOperationException on modification — common runtime surprise. Small collection details like these often lead to big debugging sessions. #Java #BackendDevelopment #Programming

Continuing my recent posts on JVM internals and performance, today I’m sharing a look at Java 21 Virtual Threads (from Project Loom). For a long time, Java handled concurrency using platform threads (OS threads)—which are powerful but expensive, especially for I/O-heavy applications. This led to complex patterns like thread pools, async programming, and reactive frameworks to achieve scalability. With Virtual Threads, Java introduces a lightweight threading model where thousands (even millions) of threads can be managed efficiently. 👉 When a virtual thread performs a blocking I/O operation, the underlying carrier (platform) thread is released to do other work. This brings Java closer to the efficiency of event-loop models (like in Node.js), while still allowing developers to write simple, synchronous code without callback-heavy complexity. However, in real-world scenarios, especially when teams migrate from Java 8/11 to Java 21, it’s important to keep a few things in mind: • Virtual Threads are not a silver bullet—they primarily improve I/O-bound workloads, not CPU-bound ones • If the architecture is not aligned, you may not see significant latency improvements • Legacy codebases often contain synchronized blocks or locking, which can lead to thread pinning and reduce the benefits of Virtual Threads Project Loom took years to evolve because it required deep changes to the JVM, scheduling, and thread management—while preserving backward compatibility and Java’s simplicity. Sharing a diagram that illustrates: • Platform threads vs Virtual Threads • Carrier thread behavior • Pinning scenarios Curious to hear—are you exploring Virtual Threads in your applications, or still evaluating? 👇 #Java #Java21 #VirtualThreads #ProjectLoom #Concurrency #Performance #SoftwareEngineering

🚀 Java 25 is bringing some seriously exciting improvements I’ve published a blog post where I break down the key features you should know about in Java 25👇 🔍 Here’s a quick preview of what’s inside: 🧩 Primitive Types in Patterns (JEP 507) Pattern matching gets even more powerful by supporting primitive types - making your code more expressive and reducing boilerplate. 📦 Module Import Declarations (JEP 511) Simplifies module usage with cleaner import syntax, helping you write more readable and maintainable modular applications. ⚡ Compact Source Files & Instance Main (JEP 512) A big win for simplicity! You can write shorter programs without the usual ceremony - perfect for beginners and quick scripts. 🛠️ Flexible Constructor Bodies (JEP 513) Constructors become more flexible, giving developers better control over initialization logic and improving code clarity. 🔒 Scoped Values (JEP 506) A modern alternative to thread-local variables, designed for safer and more efficient data sharing in concurrent applications. 🧱 Stable Values (JEP 502) Helps manage immutable data more efficiently, improving performance and reliability in multi-threaded environments. 🧠 Compact Object Headers (JEP 519) Optimizes memory usage by reducing object header size - a huge benefit for high-performance and memory-sensitive applications. 🚄 Vector API (JEP 508) Enables developers to leverage modern CPU instructions for parallel computations - boosting performance for data-heavy workloads. 💡 Whether you're focused on performance, cleaner syntax, or modern concurrency, Java 25 delivers meaningful improvements across the board. 👇 Curious to learn more? Check the link of full article in my comment. #Java #Java25 #SoftwareDevelopment #Programming #Developers #Tech #JVM #Coding #Performance #Concurrency