spring_data.tar.gz

spring_data_chapter1

spring_data_jdbc_chapter3

spring_data_jpa_chapter4

spring_data_mongodb_chapter5

spring_data_redis_chapter6

spring_data_couchbase_chapter7

spring_data_elasticsearch_chapter8

spring_data_neo4j_chapter9

spring_data_cassandra_chapter10

spring_data_geode_chapter11

spring_data_solr_chapter12

spring_data_chapter2

spring_data_mongodb_chapter5-transaction

This course will teach you how to seamlessly integrate Spring Data with various data sources, including relational and nonrelational databases, map-reduce frameworks, and cloud-based data services. 

You’ll start this course by exploring Spring Data JDBC and Spring Data JPA for efficient access to relational databases. Next, you’ll dive into NoSQL databases with Spring Data MongoDB and Spring Data Redis, venture into graph databases with Spring Data Neo4j, and explore the world of distributed databases with Spring Data for Apache Cassandra. Lastly, you’ll discover the power of Spring Data Elasticsearch. 

By the end of this course, you’ll emerge equipped with the knowledge and skills to leverage Spring Data effectively in diverse data-driven scenarios. You’ll be able to create applications seamlessly integrated with various data sources. This proficiency in Spring Data will enable you to design, build, and maintain applications that interact effortlessly with databases and data services.

Spring Data: Bridging Multiple Databases

In Neo4j, a graph node is a data entity with a unique identifier representing real-world entities in the graph database with properties and connections to other nodes through relationships.

Learn about nodes and repositories through the Spring Data Neo4j framework.

Neo4j Nodes and Repositories

Introduction to Spring Data

Spring Data in Detail

Spring Data JDBC

Spring Data JPA

Spring Data MongoDB

Spring Data Redis

Spring Data Couchbase

Spring Data Neo4j

Spring Data for Apache Cassandra

Spring Data Elasticsearch

Bank Management System

Wrapping Up

Neo4j Nodes and Repositories