Markus Kett on JAVAPRO International

Petabyte-Scale AI Memory with Serverless Java

Wed, 15 Apr 2026 07:00:01 +0000

The current wave of Generative AI innovation is built on a paradox. While models are becoming more powerful and efficient, the infrastructure required to operate them at scale is becoming increasingly wasteful. Enterprises are investing millions into compute, storage, and energy, yet a significant portion of these resources remains idle. Modern vector databases, graph systems, and caching layers are based on a monolithic architecture run as always-on clusters, consuming CPU and RAM regardless of whether data is actively accessed. Studies and industry analyses consistently show that up to 80% of compute resources in such systems are effectively wasted on idle workloads.

Next Generation Caching & In-Memory Searching

Mon, 28 Jul 2025 07:00:01 +0000

When Traditional Databases Reach Their Limits

Enterprise applications frequently face performance bottlenecks that stem from the underlying persistence layer. Despite decades of database evolution, many core applications still struggle with latency, throughput, and architectural complexity. These issues are particularly evident in systems that depend on complex join operations across multiple tables, need to process unstructured data, or must execute cross-database queries spanning disparate systems to fulfill analytical workflows.

In such environments, it is common to see a combination of various technologies being deployed in tandem: a traditional relational database, a distributed cache, a NoSQL database, and sometimes a dedicated search server such as Elasticsearch. While each of these systems addresses a specific technical challenge, their co-existence leads to architectural fragmentation, high infrastructure costs, duplicated data models, and increased development and maintenance efforts. Moreover, the overall latency and resource usage often remain suboptimal due to inherent I/O-bound limitations and serialization overheads between systems.

EclipseStore: The Evolution of Java Persistence

Mon, 12 May 2025 11:24:29 +0000

Database development in Java has always been a challenge, often feeling like a battle against mismatched paradigms. From the start, developers wrestled with complex mappings and performance bottlenecks when integrating Java with databases. EclipseStore, an open-source project under the Eclipse Foundation, was created to change this. Its mission is to deliver a Java-native persistence layer that feels like an integral part of the language, not a workaround for database limitations. By storing Java objects directly, it aims to simplify and accelerate development, aligning persistence with Java’s core strengths.

EclipseStore TAKES CONTROL OF CONCURRENCY

Fri, 29 Nov 2024 14:45:02 +0000

In the world of data management, ensuring data integrity and consistency is paramount, especially for mission-critical applications in finance, healthcare, and other sensitive sectors. This is where the concept of ACID comes in.

ACID: The Bedrock of Reliable Data

ACID stands for Atomicity, Consistency, Isolation, and Durability. These properties are essential for any database system that handles transactions. Let’s break down what each means:

Atomicity: An operation within a transaction is either all successful or all fails. This ensures that the data remains consistent.
Consistency: The database enforces data integrity rules. Transactions may not leave the data in an invalid state.
Isolation: Transactions execute as if they were isolated from each other. Changes made in one transaction are invisible to other ongoing transactions until the first one is committed.
Durability: Once a transaction is committed, the changes are permanently persisted in storage. This ensures that data is not lost even in case of system crashes or power failures.

EclipseStore: Speed Meets Simplicity