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MAY

How To Create Domain-Specific Database Servers

May 5, 2022

5:00 PM - 6:00 PM

There are a handful of design patterns for microservices when it comes to domain-specific databases. However, they all assume a physical separation between microservices and their databases.

What if we embedded the database within our microservice, created methods to access its data with NoSQL APIs, and exposed them via GraphQL over HTTP? Well, we'd have our own database-as-a-microservice (DBaaMS).

In this developer webinar, we're going to introduce the DBaaMS concept and walk through the code of a sample database microservice built with Quarkus, SmallRye, and FairCom DB. How should databases be deployed for microservices? It's a common question because shared data access isn't necessary when all reads and writes must go through the same microservice. Then there is GraphQL, a simple alternative to SQL. What if you could embed a NoSQL database in your microservice, configure GraphQL endpoints on top of it, and synchronize it with remote databases/devices using MQTT?

The database-per-service pattern ensures loose coupling, but it can be further refined by embedding NoSQL databases within microservices and providing web and mobile applications with access to data via GraphQL over HTTP. In addition, we can leverage MQTT to support Saga and CQRS patterns, and in Industrial IoT use cases, to capture sensor data. If the primary function of microservices is to provide web and mobile applications with data access, and if each microservice "owns" its data, do you even need a remote database server? The short answer is no. We could opt for a far more elegant solution, embedding a NoSQL database with our microservice and exposing it via GraphQL.

In this webinar, we'll show you how to build and deploy a lightweight, domain-specific database server as a microservice with GraphQL endpoints using Quarkus, Smallrye, and FairCom DB.

Powering microservices with embedded databases
Creating domain-specific GraphQL schemas and queries
Integrating IoT data into microservices with MQTT

Duration: 1 hour, 3 minutes. Available On-Demand.

Speakers

Shane Johnson

Shane Johnson is a former Java developer and architect specializing in distributed systems. Prior to joining Faircom, he led technical marketing for Red Hat, followed by product marketing at Couchbase and MariaDB.

Hosts

FairCom

FairCom EDGE simplifies the integration of sensor and machine data at the source – whether it’s a factory, water treatment plant, oil platform or wind farm. The world’s first converged IoT/Industrial IoT hub, FairCom EDGE unifies messaging, persistence and analytics with an all-in-one solution – complete with browser-based administration, configuration and monitoring.FairCom EDGE supports MQTT and OPC UA for machine-to-machine (M2M) communication, SQL for interactive analytics and HTTP/REST for real-time monitoring. It continuously retrieves data from sensors and machines with OPC UA support, and receives messages from those with MQTT support. The data is automatically parsed, persisted and made accessible via MQTT and SQL.