When building up search engines, indexing tons of data into a schema-less, distributed data store, Elasticsearch has always been a favourite tool of mine.

In addition to its core features, it also offers tools and documentation for us developers when we need to write integration tests for our Elasticsearch powered Java applications.

In the following tutorial I’d like to demonstrate how to implement a small sample application using Elasticsearch under the hood and how to write integration-tests with these tools for this application afterwards.

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When integrating a Neo4j database into a Java application a developer often needs to map nodes and edges of the graph to corresponding Java classes of the domain model.

Neo4j OGM eases this work and allows us to map our domain objects to the graph database using simple annotations – similar to the Java Persistence API (JPA) for relational database management systems.

In the following tutorial I’d like to demonstrate how to use Neo4j OGM to build a simple train timetable planner and a permission system mapping between graph, nodes, edges and POJOs.

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HipChat is Atlassian’s alternative to Slack and its solution to team collaboration chats. Atlassian Connect offers developer tools to bootstrap applications, connect to Atlassian’s cloud products with easy and in combination with HipChat’s REST APIs allows us to write integrations for such a chat server in no time.

In the following tutorial I’d like to show how to write an integration within a few steps using Atlassian Connect, Node.js and Express and how to connect the integration to a HipChat server.

Finally on the one hand I’m going to explain how to speed up local development with ngrok, an in-memory database and nodemon for automatic application restarts and on the other hand I’m going to demonstrate how to configure the application for production, running with a Redis key-value store on Heroku.

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Often in the life of developer’s life there is a scenario where using a relational database tends to get complicated or sometimes even slow – especially when there are fragments with multiple relationships or multiple connections present. This often leads to complex database queries or desperate software engineers trying to handle those problems with their ORM framework.

A possible solution might be to switch from a relational database to a graph database – and – neo4j is our tool of choice here. In the following tutorial we’re going to implement several examples to demonstrate the strengths of a graph database .. from a route planner to a social graph.

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