Alternative Databases Beyond RDBMS
The value of excellent data management cannot be emphasized in our increasingly data-driven world. Every day, innumerable organizations and individuals generate and depend on massive volumes of data, which include customer information, financial records, product inventories, and other information. As the volume and complexity of data increase, also rises the demand for efficient and scalable systems to store, retrieve, and modify this data. Databases come into play in this situation.
What is a database?
A database is a structured collection of data that is organized, stored, and managed so that access, retrieval, and manipulation are simple. Databases are the foundation of numerous applications and systems, allowing them to handle data efficiently. They come in various shapes and sizes, but the most well-known and widely used type is the Relational Database Management System (RDBMS), which manages and queries data using SQL (Structured Query Language). For decades, SQL RDBMS such as MySQL, PostgreSQL, and Microsoft SQL Server have been the go-to solution for managing structured data.
Although SQL RDBMS has been the standard choice for database administration, alternatives have evolved to meet increasing data requirements. In this article, we will explore some of these alternatives to SQL RDBMS and the unique strengths they bring to the table, offering solutions for specific use cases and data requirements. Whether you’re dealing with extensive data, NoSQL databases, or distributed systems, there’s a database alternative that may be the perfect fit for your needs.
Five futuristic databases
Dolt
Dolt is an open-source, version-controlled relational database. It combines the power of SQL databases with the ability to track changes in the data over time, much like a version control system. This database would be like if MySQL and Git had a baby. Most importantly, it allows you to create branches from the main database, where you can experiment with new data without breaking things. It makes it easy to analyse the diff between changes, and when everything looks good, the changes can be merged back into the main branch. And it’s done with the same conventions found in Git that virtually every developer is familiar with.
Fauna DB
Fauna DB is a globally distributed, serverless, and transactional NoSQL database. It offers a multi-model approach that combines document, graph, and relational data models. It’s effortless use like a document database similar to MongoDB, but unlike a document database, it supports features like native joins, which is the number one missing feature in document databases, and that means Fauna is more well suited for complex relational data like social graphs. To interact with it, it has its custom query language called FQL but also comes with a GraphQL API
Minds DB
Minds DB is a machine learning system that offers automated machine learning (AutoML) capabilities. It aims to simplify and democratize machine learning by providing an intuitive interface for creating predictive models without extensive coding or machine learning expertise. It can also integrate with your existing machine learning models or those from third parties like hugging face or open AI.
Planet Scale
Planet Scale is a serverless platform for MySQL. Considering YouTube, it uses MySQL. However, in 2010, when it was getting popular, it took a lot of work to scale, at least for an app with millions of simultaneous connections. Instead of switching to a NoSQL document database, they developed a library called Vitess, which makes some tradeoffs to scale MySQL horizontally. And Planet scale is built upon this technology. It offers a wholly managed database that is compatible with Vitess and is accessible through an elegant dashboard along with SDKs. It also works well with tools like Prisma.
YugaByte DB
Yugabyte DB is an open-source, distributed SQL database with global scalability and high availability. It is compatible with PostgreSQL and provides strong consistency. Its goal is to scale infinitely in the cloud but attempt to support all the native features in Postgres, which is challenging in a cloud-native environment. You can use a multi-cloud strategy to host your database on multiple clouds simultaneously, eliminating the dreaded vendor lock-in issue.
Now, you have five different futuristic databases to choose from for your next project. These databases cater to specific use cases and data requirements, offering alternatives to traditional SQL RDBMS for managing data effectively in our data-rich world.
