There are several types of datastores out there for use today, and it’s likely that whatever datastore your company is using was implemented because it’s what your programmers are used to using. That’s not a bad thing, but there might be better options that complete the tasks you need done in a more efficient manner. In this installment of our series on datastores, we will discuss object and edge-based systems, what they are best used for and what they are not good at.

Object databases are good when you have a lot of data about individual things. If you go back to the article on NoSQL, there’s a great example of how Facebook uses individual profiles to correlate data. Not relate, because this isn’t relational, but all data under one profile belongs to that person and that’s how it is stored. MongoDB and CouchDB are both examples of object-oriented databases.

Now, the problem with object-oriented databases happens when you need a way to correlate data from multiple objects. In a relational database, you can complete this task, essentially, with a single query. But in an object-oriented database, it’s going to take 3-4 calculations to get the list or return the answer you are looking for. This is because you’re not looking by the object anymore, you’re looking for one attribute of an object, which makes it more complex.

Another problem you can run into with object-oriented databases is querying for a specific piece of data and instead getting a slew of information or at least walk down into it. As with all things object-oriented, when you ask for a banana, you end up getting the whole gorilla holding it. You may not have wanted the whole gorilla, but that’s what you were given so now you must work with it.

The key thing to remember with object-oriented databases is that the data is stored under an object. Whether that object is a person’s Facebook profile, a city, a state, a country, a car, a brand of a product doesn’t matter. All the data underneath the object belongs to the object, it’s information about a specific item or person, which is the root of all the other data. So, when you’re looking at these objects and the data around them, it’s very efficient.

Edge databases are designed to work with edge computing to process and store data faster. Edge computing can be defined as, “a part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information.” Essentially, edge computing uses algorithms that run locally on devices to make them run more efficiently and quickly.

Edge databases store data for edge computing. This enables more efficient, real-time applications that are critical to companies. Virtual and augmented reality, self-driving cars, smart cities and building-automation systems require fast processing and response. Having that data in an edge database makes edge computing possible.

“Edge computing has evolved significantly from the days of isolated IT at ROBO [Remote Office Branch Office] locations,” says Kuba Stolarski, a research director at IDC, in the “Worldwide Edge Infrastructure (Compute and Storage) Forecast, 2019-2023” report. “With enhanced interconnectivity enabling improved edge access to more core applications, and with new IoT and industry-specific business use cases, edge infrastructure is poised to be one of the main growth engines in the server and storage market for the next decade and beyond.”

Increasing processing in the edge created the need for edge databases. The growth in this area of IoT has allowed for better responses in applications that need instant computing. Edge databases are designed specifically for edge computing and looking at specific sets of data. They are object-oriented in nature, not relational, and very efficient at what they do.

Essentially, an edge database is a type of object-oriented database, but because it is becoming more of a necessity to various sectors of business, it is pertinent to have a solid understanding of what they are and what they are good for. Both edge and object-oriented databases are efficient at what they do, and they are useful in a variety of situations. Be sure to know the difference between all types of datastores when you implement a data storage system as this will ensure your data remains safe, protected, and used properly.