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World Congress 2022 • Jun 15, 2022

Build ultra-fast In-Memory Database Apps and Microservices with Java

Markus Kett

Stop letting ORM bottlenecks crush your Java microservices. Discover how bypassing relational mapping for Java-native persistence delivers microsecond query execution and cuts cloud costs by 90%.

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#1 about 5 min

The impact of latency on modern Java applications

How the demand for real-time data processing exposes strict performance bottlenecks in standard enterprise programming operations.

#2 about 4 min

Shifting from monolithic architectures to microservices and containers

The ongoing evolution of infrastructure toward cloud-native microservices introduces advanced and automated container management demands.

#3 about 2 min

Why traditional Java runtimes struggle with microservice environments

Application servers and standard JVM packages carry heavy memory footprints and slow startup times unsuitable for volatile containers.

#4 about 3 min

Adopting modern microservice frameworks for lightweight Java runtimes

How frameworks like Helidon and Micronaut replace heavyweight application servers to streamline development for containerized environments.

#5 about 3 min

Enhancing Java startup speed with GraalVM native images

Using GraalVM to compile Java into native machine code drastically reduces application startup time and system memory footprint.

#6 about 2 min

Comparing serverless deployment and Kubernetes operational cloud tradeoffs

Evaluating the operational capabilities and cost implications of running workloads on managed clusters versus serverless execution endpoints.

#7 about 6 min

The object-relational impedance mismatch in standard database programming

How standard persistence APIs and relational databases fundamentally struggle to map and store intrinsically complex software object graphs.

#8 about 3 min

Accelerating data processing via resilient in-memory computing strategies

Caching domain data directly into server memory mitigates expensive serialization computations and external disk access latencies.

#9 about 2 min

Simplifying software architectures using the system prevalence pattern

Loading system state dynamically into memory while exclusively relying upon automated persistence snapshots replaces relational structures entirely.

#10 about 9 min

Introducing MicroStream for rapid memory object graph persistence

An open-source native Java library facilitates selectively writing data subgraphs natively to disk or remote blob storage mediums.

#11 about 4 min

Implementing code state persistence without domain structural restrictions

Utilizing unannotated standard framework classes enables software engineers to constrain memory limits through robust lazy loading functionalities flawlessly.

#12 about 3 min

Navigating architecture limitations and future clustered storage variants

While initially optimized for isolated runtimes, upcoming networking capabilities introduce highly available distributed data nodes for concurrent writes.

#13 about 4 min

Slashing IT infrastructure costs by adopting memory persistence

Refactoring rigid legacy relational systems towards lightweight local memory clusters achieves significant cost reductions within deployed cloud platforms.

Matching moments

3:35 min

Optimizing Java startup processes for fast serverless workloads

Daniel Oh Daniel Oh +1 · World Congress 2024

2:37 min

Optimizing container workloads with Quarkus and lightweight JVMs

Niklas Heidloff · LIVE

2:20 min

Overcoming Java cold starts using the Quarkus framework

Alex Soto Alex Soto · LIVE

2:36 min

Modern application stacks and real-time data requirements

Tim Faulkes · LIVE

2:37 min

Processing data at microsecond speeds with Java Streams

Markus Kett Markus Kett · World Congress 2024

11:17 min

Optimizing application performance via GraalVM native images

Josh Long · LIVE

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