Oracle has released Java 27, incorporating nine JDK Enhancement Proposals designed to boost developer productivity and application performance, the company says. A key focus of the new release is bolstering post-quantum cryptography, with Java 27 introducing hybrid key exchange for TLS 1.3 to safeguard sensitive data against future decryption threats.
“Java’s security, reliability, and enterprise scale make it a critical foundation for AI agents that require trusted access to business systems and sensitive data,” notes IDC’s Arnal Dayaratna. Alongside these advancements, Oracle is also adding Jipher 20 to its Java Verified Portfolio, assisting customers in meeting FIPS 140 compliance standards.
Java 27 Strengthens Post-Quantum TLS 1.3 Key Exchange
Java 27 incorporates a hybrid key exchange mechanism for Transport Layer Security 1. 3, a critical step in preparing digital communications for the advent of quantum computing. This new feature, detailed within JDK Enhancement Proposal 527, allows systems to negotiate cryptographic keys using both traditional algorithms and post-quantum counterparts, offering a layered defense against future decryption threats. The hybrid approach ensures continued secure communication even if current encryption methods are compromised by advances in quantum computing power.
This implementation isn’t merely theoretical; Oracle has integrated Jipher 20 into its Java Verified Portfolio, providing customers with a FIPS 140-3 validated cryptographic module for Java applications, according to the company. These proposals encompass a range of improvements, from optimizations within the Java Virtual Machine to new APIs for streamlined development. Oracle’s cloud infrastructure, Oracle Cloud Infrastructure was the first to support Oracle JDK 27 demonstrating a commitment to providing a fully integrated development and deployment environment.
The move towards post-quantum cryptography reflects a growing awareness of the potential risks posed by quantum computers to current encryption standards. The “harvest now, decrypt later” threat, where malicious actors collect encrypted data with the intention of decrypting it once quantum computers become powerful enough is a significant concern for organizations handling long-term sensitive information.
“Java 27’s tools for AI development and post-quantum cryptography strengthen its role in application development and help organizations prepare for a new generation of applications and security threats in the agentic era,” said Arnal Dayaratna, research vice president, software development, IDC. Oracle’s approach to post-quantum cryptography is not a one-time fix, but rather a roadmap for ongoing adaptation.
The company states it is executing on a plan to bring comparable capabilities to future long-term support JDK releases, ensuring customers can proactively protect their applications and data with minimal disruption, the firm reports. “For more than three decades, Java has helped developers build powerful, reliable, and secure applications,” said Georges Saab, senior vice president, Oracle Java Platform and chair, OpenJDK governing board.
“Java 27 continues that proud tradition by providing a stable foundation for today’s enterprise workloads and innovative AI and post-quantum cryptography capabilities.” The development of these features has been a collaborative effort, drawing on contributions from the global Java developer community through the OpenJDK and Java Community Process. This open-source model fosters innovation and ensures that Java remains a relevant and adaptable platform for the evolving needs of enterprise software development.
The integration of Jipher 20 and the advancements in post-quantum key exchange within Java 27 represent a step towards securing digital communications in the face of emerging quantum threats, and solidifying Java’s position as a cornerstone of modern enterprise infrastructure.
For more than three decades, Java has helped developers build powerful, reliable, and secure applications.
Georges Saab, senior vice president, Oracle Java Platform and chair, OpenJDK governing board
JEP 538 Enhances PEM Cryptographic Object Handling
Java 27 incorporates enhancements to PEM encoding of cryptographic objects as detailed in JEP 538, streamlining secure handling of widely used cryptographic material and improving interoperability with existing security infrastructure. This update addresses a critical need for seamless integration within modern authentication, encryption, and certificate-management systems, particularly as enterprises deploy increasingly complex AI applications demanding robust security protocols. The move facilitates easier integration for Java applications, supporting secure enterprise AI deployments and bolstering defenses against evolving threats.
Beyond simplifying integration, JEP 538’s focus on PEM encoding directly supports compliance efforts, a key concern for organizations operating in regulated environments. Oracle’s inclusion of Jipher 20 within the Oracle Java Verified Portfolio (JVP) further underscores this commitment, assisting customers in deploying Java applications within FIPS 140-regulated environments, the company states.
This verification process ensures that Jipher 20 meets stringent security standards, providing a trusted foundation for sensitive data handling. The features within Java 27 are a product of ongoing collaboration between Oracle and the Java developer community through OpenJDK and the Java Community Process demonstrating a commitment to open innovation and continuous improvement.
Java’s security, reliability, and enterprise scale make it a critical foundation for AI agents that require trusted access to business systems and sensitive data.
Arnal Dayaratna, research vice president, software development, IDC
Vector API (JEP 537) Accelerates AI and Data Workloads
The Java 27 release incorporates the Vector API (JEP 537), an incubator feature designed to substantially improve performance for data-intensive tasks without requiring developers to write specialized native code. This API accelerates analytics, artificial intelligence inference, and workloads common in scientific computing and media processing by using single instruction, multiple data (SIMD) capabilities present in modern processors. By enabling greater throughput, the Vector API aims to deliver more insights and value from existing hardware, a critical consideration as computational demands continue to escalate.
This performance boost stems from the API’s ability to operate on multiple data elements simultaneously, a technique known as vectorization. Traditionally, achieving such performance in Java required developers to resort to languages like C++ or utilize native libraries, introducing complexity and hindering portability. The Vector API abstracts away these complexities, allowing Java developers to write code that automatically benefits from vectorization when executed on supporting hardware.
Oracle reports that this approach improves Java application performance while maintaining the portability, maintainability, and security expected from the Java platform. This is particularly relevant for AI workloads that coordinate numerous parallel tasks, including model calls, data retrieval, enrichment, ranking, orchestration, and real-time decisioning. Beyond performance gains, the Vector API also contributes to improved resource utilization. As a result of the API’s optimizations, customers can potentially run existing applications on newer JDK versions with a reduced memory footprint.
For organizations managing large Java estates, this translates to improved application density, lower infrastructure costs, and increased scalability for cloud services and microservices, as well as data-intensive and AI-enabled workloads. Delivered in stages, Project Valhalla aims to make Java data representation denser and more efficient while preserving the Java programming model. This project provides developers and enterprises with early visibility into future improvements for data-heavy applications.
Oracle is also simultaneously advancing Project Leyden, focused on improving startup time, time to peak performance, and memory footprint, including through ahead-of-time compilation, by the company’s account. The integration of JEP 533, Structured Concurrency (Seventh Preview), complements the Vector API by reducing development risk for cloud, microservices, and AI-enabled applications. This feature enables developers to build scalable, resilient services with fewer concurrency defects, an important benefit for complex AI systems.
JEP 527: Post-Quantum Hybrid Key Exchange for TLS 1.3: Helps organizations strengthen the protection of sensitive data and business-critical communications against “harvest now, decrypt later” threats while enabling developers to meet evolving cryptographic requirements with minimal application disruption.
Compact Object Headers (JEP 534) Improve Memory Efficiency
Enabling compact object headers by default within Java 27 demonstrably reduces Java Virtual Machine memory overhead, a change that benefits applications undergoing modernization efforts. This optimization, delivered through Java Enhancement Proposal 534, allows existing applications to function on the newest Java Development Kit while simultaneously decreasing their memory footprint, Oracle claims. The reduction in memory usage is not merely theoretical; it directly impacts scalability, especially for data-intensive and AI-enabled workloads where efficient resource allocation is paramount.
This project isn’t simply about shrinking memory usage, but about fundamentally altering how Java handles data, giving developers and enterprises early insight into future improvements for applications dealing with large datasets. Valhalla’s approach focuses on preserving the established Java programming model while simultaneously enhancing performance, a delicate balance for maintaining compatibility and minimizing disruption during upgrades.
Oracle’s commitment to this evolution is further demonstrated by its concurrent advancement of Project Leyden, which targets improvements in startup time, peak performance, and overall memory footprint through techniques like ahead-of-time compilation. Beyond the immediate memory savings, the change in object header structure facilitates a more streamlined approach to data management, influencing how applications interact with memory at a fundamental level. This is particularly relevant given the increasing complexity of modern applications, which often juggle multiple data structures and require rapid access to information.
The ability to reduce memory overhead without sacrificing performance is a significant advantage in competitive environments, allowing developers to extract more value from existing hardware and reduce operational expenses. The impact of compact object headers extends beyond simple efficiency gains, influencing the broader ecosystem of Java development and deployment.
Oracle’s cloud infrastructure, which was the first to support Java JDK 27, is designed to maximize the benefits of these optimizations, the company says. This close relationship between the Java platform and the underlying infrastructure allows for a more holistic approach to performance tuning and resource management.
See today’s quantum computing news on Quantum Zeitgeist for the latest breakthroughs in qubits, hardware, algorithms, and industry deals.
