Microservices are applications composed of several independently deployable services. Every microservice controls its data. It doesn't care about how other components are going to use that data. This architecture gives you greater agility in rolling out new application features.
With a microservices architecture, applications can be broken down and developed through a collection of loosely coupled services that allow continuous development without having to redeploy the entire application.
The emergence of IoT, Geo distributed distribution, minimizing latency across international boundaries, distributed data, continuous deployment, and the need for applications to use diverse data types and models for different functions forces you to go beyond a monolith architecture.
To support the new standards, databases will have to be easy to use, simple to set up, multi-model, and enable seamless polyglot persistence to support microservice DevOps teams. By nature, microservice applications are complex, but you can reduce that complexity at the database layer to manage it throughout your application.
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Most databases can fit into a microservices architecture one way or another. The idea database for such a system is one that includes the following features:
- Schemaless. You can change the foundation of your data model multiple times. Changing the schema once you are in production is baked into the cake, so you need a database that is as flexible with your schema as can be.
- ETL Replication. To keep services independent from one another, you need their data to stand on its own. This requires a native ETL tool that will ferry information to and from each service.
- Supports Transactional Data (ACID). In a microservices architecture, at least one of the services will need ACID compliance. You need to have the ability to process fully transactional operations on demand.
- Easy to set up and easy to use. Microservice teams are small. Even if they are part of a large app or a large organization, the groups are small, so they need a database that requires as little work as possible.
Microservices are complex. You need a database that can manage complexity, so you are free to scale out at the application level. To keep things simple at the database layer, your database must be:
Multi-model. Different services will want to take in various forms of data. The ability to break apart your services into graph data, document data, key-value types, time-series, and more is at the heart of agility and scalability.
Non-relational. The complexity of tables, joins, and piecing together bits and pieces of data fragments scattered throughout multiple servers across the world can make your application very complicated and prone to error. Non-relational databases eradicate the use of putting together tables to serve a query and keeps complexity to a minimum.
Fully Loaded. MapReduce, full-text search, automatic caching, GUI, versioning, even a storage engine are things that you might have to add on to your database. A database with all of this built-in reduces your need for additional moving parts.
Distributed. A distributed database has the advantages of not needing to be chained to a single server. Microservices are distributed and used primarily on the cloud. A database built to be distributed is the ideal fit for both.
Data is the lifeblood of a business, and your database is the heart that pumps it to the entire body of the organization. As everything expands, how do you efficiently reorganize the structure of your systems to make sure everything is running with maximum efficiency and minimum complexity?
This webinar talks about the evolution of a monolith architecture to microservices, and the benefits of localizing roles in your IT systems to microsystems to redistribute complexity while boosting productivity, efficiency, and capacity.
See the Webinar
- Microservices as the Solution to the Monolith Challenges
- Monolithic Architecture vs Microservices: Advantages and Challenges
- Core Principles of Microservices Databases