Spring

Building Spring Boot Applications with YugabyteDB: A Guide to Creating Native Images Using GraalVM

Building Spring Boot Applications with YugabyteDB: A Guide to Creating Native Images Using GraalVM

This blog provides a guide to building Spring Boot applications with YugabyteDB using GraalVM’s ahead-of-time (AOT) compilation to generate a native image. The guide covers the necessary prerequisites and steps to trigger the native build, including how to handle dependencies lacking reachability metadata with explicit runtime hints.

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Change Data Capture (CDC) Using a Spring Data Processing Pipeline

Change Data Capture (CDC) Using a Spring Data Processing Pipeline

Change Data Capture (CDC) is a technique to capture changes in a source database system in real-time. The goal is to stream those changes as events through a data processing pipeline for further processing.

CDC enables many use cases, especially in modern microservices-based architecture that involves a lot of bounded services. It is the de-facto choice for use cases such as search indexes, in-memory data cache, real-time notifications, data sync between sources,

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Connecting a Spring Boot Application to YugabyteDB Managed and Deploying It to Kubernetes on minikube

Connecting a Spring Boot Application to YugabyteDB Managed and Deploying It to Kubernetes on minikube

Spring Boot is one of the most popular frameworks for building cloud native applications. It makes configuring an application easy and offers tons of starters to get you off the ground quickly. Each Spring Boot application is stand-alone and self-contained, which makes them easy to deploy in a distributed fashion – to containers or, even better, on Kubernetes.

YugabyteDB Managed (formerly Yugabyte Cloud) is Yugabyte’s DB-as-a-service and is a perfect match for Spring Boot applications,

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Spring Data YugabyteDB – Getting Started!

Spring Data YugabyteDB – Getting Started!

Spring Data modules are widely used Spring Framework projects for implementing database access in Java applications. Spring Data provides consistent and familiar APIs for querying the data by supporting Data Repository and Template methods, reducing the boilerplate code required for establishing database connection and queries.

For developers and architects, the standard set of APIs provided by Spring Data abstracts away the need to learn the database-specific query language, reducing ramp-up time and increasing developer velocity.

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Distributed SQL Summit Recap: Cloud Native Spring for Relational Databases

Distributed SQL Summit Recap: Cloud Native Spring for Relational Databases

Editor’s note: Below is the final recap from last year’s event. There’s still time to join us live for the upcoming Distributed SQL Summit, Jan 20-22 in India Standard Time.

At the Distributed SQL Summit 2020, DaShaun Carter, formerly a Tanzu Solution Engineer at VMware presented the talk, “Cloud Native Spring for Relational Databases”.

In the talk, DaShaun takes us down about a possible path to distributed SQL,

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Building Serverless Applications Using Spring Boot, AWS Lambda, and YugabyteDB

Building Serverless Applications Using Spring Boot, AWS Lambda, and YugabyteDB

Introduction to Serverless Applications

Serverless applications allow developers to run code without having to provision or manage any servers; developers can just concentrate on implementing the business logic of their applications.

As workloads move to the cloud, serverless applications are gaining tremendous popularity with developers. Serverless frameworks allow developers to program for the cloud to take advantage of elastic scaling for workloads and provide cost benefits of using pay-for-use features, only getting billed for compute time they consume.

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Run the REST Version of Spring PetClinic with Angular and Distributed SQL on GKE

Run the REST Version of Spring PetClinic with Angular and Distributed SQL on GKE

Java developers know that Spring Data makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. When YugabyteDB is combined with Spring, Java developers are able to leverage their familiarity with PostgreSQL while gaining the added benefits of distributed SQL. These “out-of-the-box” benefits include geo-data distribution, high performance, and horizontal scalability, which are impossible or difficult to achieve with monolithic SQL databases.

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Scaling Relational Spring Microservices Without Load Balancers

Scaling Relational Spring Microservices Without Load Balancers

This article was originally posted on JAXenter.com.

Modern cloud native applications demand relational databases to be highly available while being able to scale to millions of requests (RPS) and thousands of transactions per second (TPS) on demand. This is becoming essential to meet the seamless experience demanded by business applications and their users. High availability and scalability in NoSQL databases like Apache Cassandra and MongoDB are well understood, but have been challenging problems to solve in relational databases.

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