Markus Kett
Build ultra-fast In-Memory Database Apps and Microservices with Java
#1about 4 minutes
The challenge of real-time data in modern applications
Modern applications for AI, IoT, and machine learning require processing vast amounts of data in real-time, questioning if traditional Java and databases are fast enough.
#2about 5 minutes
How cloud architecture evolved from monoliths to microservices
The industry shifted from monolithic applications on physical servers to containerized microservices orchestrated by platforms like Kubernetes.
#3about 7 minutes
Java's adaptation for cloud-native and serverless computing
Java became suitable for microservices through lightweight frameworks, GraalVM native images for fast startups, and serverless function platforms.
#4about 8 minutes
The object-relational impedance mismatch in persistence
Storing complex Java object graphs in relational or NoSQL databases creates an impedance mismatch, requiring costly data conversion and mapping for every operation.
#5about 7 minutes
Introducing the system prevalence pattern with MicroStream
The system prevalence pattern keeps the entire application state in memory for ultra-fast queries and uses snapshots for persistence, a concept implemented by MicroStream.
#6about 7 minutes
Exploring the MicroStream persistence engine architecture
MicroStream is a Java-native persistence library that serializes object subgraphs to various storage backends without mapping, supporting lazy loading and class versioning.
#7about 5 minutes
MicroStream usage patterns, limitations, and benefits
MicroStream operates as a single-node storage solution within the JVM process, offering significant performance gains and cost savings but does not use SQL.
#8about 1 minute
Combining persistence strategies in a microservices world
Microservice architectures allow you to choose the best persistence technology for each service, enabling combinations of MicroStream with relational databases or search engines.
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