World Congress 2024 Aug 20, 2024 Session details

Databaseless Data Processing - High-Performance for Cloud-Native Apps and AI

Markus Kett

Stop letting databases bottleneck your Java apps. Eliminate ORMs entirely. Learn how EclipseStore treats object graphs as in-memory databases to deliver microsecond queries and cut costs by 90%.

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#1 about 3 min

Modern application performance and efficiency requirements

Modern applications require optimal performance combined with strict cloud cost reductions and lower energy consumption.

#2 about 3 min

Impedance mismatch between object models and relational databases

The fundamental incompatibility between object-oriented programming structures and traditional relational database tables prevents direct translation and slows computing execution.

#3 about 6 min

Complexities of object-relational mapping and distributed architectures

Using object-relational mapping frameworks alongside layered distribution caches to mitigate database bottlenecks heavily compounds architectural overhead.

#4 about 2 min

High cost of cloud database servers versus object storage

Dedicated cloud database hosting necessitates expensive compute processing units while basic object storage delivers cheap unmanaged file capacity.

#5 about 3 min

Processing data at microsecond speeds with Java Streams

In-memory object graphs structurally circumvent translation overhead and reduce latency significantly when sequentially queried using native data streams.

#6 about 4 min

Persisting native Java objects efficiently with Eclipse Store

Saving real in-memory object hierarchies directly into binary file formats eliminates operational scaling limits natively across enterprise platforms.

#7 about 4 min

Simplifying distributed architecture with stateful object graphs

Extricating cluster database dependencies minimizes infrastructure sprawl and empowers core language elements to efficiently manage concurrency replication instead.

#8 about 3 min

Performance benchmarks of relational databases against object storage

Bypassing legacy query translation logic to directly process complex in-memory types produces execution speeds far surpassing cached database interactions.

#9 about 6 min

Architectural benefits and implementation challenges of databaseless systems

Abstracting complex databaseless storage eliminates legacy operational components but concurrently mandates critical paradigm shifts like drafting unique microservice endpoints.

#10 about 1 min

Licensing and enterprise availability of Eclipse Store

The open-source core data persistence utility permits extensive local deployment while separately licensing optional commercial tooling tailored for massive production sets.

Matching moments

2:34 min

Simplifying enterprise architecture with database-less data processing

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8:06 min

Introducing MicroStream for rapid memory object graph persistence

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7:13 min

Simplifying offline data persistence using AWS Amplify DataStore

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2:36 min

Modern application stacks and real-time data requirements

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5:13 min

The object-relational impedance mismatch in standard database programming

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3:35 min

Optimizing Java startup processes for fast serverless workloads

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