How To understand Managed vs. Unmanaged Database Deployments and How to Do It

Whether you’re upgrading an existing database or designing a new system, it’s essential to understand what kind of data comes from which source. Understanding the ins and outs of profiling and monitoring data is only made more challenging by the fact that modern databases are far more complex than ever. In this blog post, we take a look at some of the key differences between managed and unmanaged database deployments, how to understand them, and how to implement them properly in your own environment. Operational challenges often drive the adoption of new technology. For example, in the past decade or so, relational databases have become well entrenched in most businesses – but not everyone has been able to adopt them quickly enough. In this blog post, we take a look at some of the key differences between managed and unmanaged database deployments, how to understand them, and how to implement them properly in your own environment.

Differences between Managed and Unmanaged Database Deployments

Managed databases are built around foundation data storage systems, while unmanaged databases often rely on an application’s own data storage infrastructure. The main difference between managed and unmanaged database deployments is the way data is stored in the system. In managed databases, data is stored in your own data store, while in unmanaged databases, data is stored in a cloud-based service. You can also notice the difference when you look at the way data is distributed across your systems. In managed databases, most data is stored on the same physical server, while in unmanaged databases, data is spread across several physical servers. This seems like a small difference, but when you factor in the scale of your business — and especially the way your business uses data — it can add up to a big difference in how you implement your solution. The vast majority of organizations don’t even know they have a difference at all.

How To understand Managed vs. Unmanaged Database Deployments

Managed databases are user-friendly and efficient. Data is organized into data tables and each table has a unique name. You can also see this in action when you look at your control files. Your control files are the source code for your applications — and as such, they’re accessible from any computer that has a browser. An unmanaged database, on the other hand, is more of a mystery. You can’t see the table name or even see what data is being stored in that table. You have no idea how many tables your application uses — or even if that table is used at all. An unmanaged database can be challenging to understand and set up, but it’s also essential to implement. In order to speed up implementation, many organizations are opting to use a managed database, either in-house or with an internal partner. This decision, though, comes with its own set of challenges.

Differences between Managed and Unmanaged Database Implementations

One of the most significant differences between managed and unmanaged database implementation is the way data is structured and structured is consumed. In managing databases, data is organized into tables, each of which may or may not have unique names. In an unmanaged database, data is often broken down into smaller chunks or files, which are saved in a variety of formats, such as text, spreadsheet, or database file. Although each format has its own qualities, the main difference between managed and unmanaged database implementations are in the way data is organized and structured.

Conclusion

Unmanaged databases are a mix of structured data and unstructured data, meaning you don’t necessarily know what data is being stored in each location. Like any other type of data, you want to ensure that data is clean, clear, and consistent. Managed databases have these three qualities, while unmanaged databases lack one: fragmented data. Managed databases are great for quick, low-volume analyses, while unmanaged databases are the perfect fit for more steady-state workloads. Even those situations, where data is highly fragmented, have been solved with one or two operators. Knowing the difference between managed and unmanaged databases is crucial to success.