Data, that is channeled from one medium to another every now and then is eligible for transformation often, which has sparked the debate as to whether databases or data lakes are the right options and what you should be using.
Data Scientists, Analysts, and tech professionals share a common interest in these technologies. Businesses on every scale are interested in knowing the differences between data lakes and a database.?
To ascertain this difference, we need to understand the basic difference between both these technologies and if they are related at all.
Data lakes on one hand have been growing in popularity these days. These technologies are often compared with data warehouses. But it’s important to realize that both these technologies have a few differences and can?t be used the same way.
On the other hand, a database refers to such a structured set of data that could be withheld on a computer. This data is easily accessible in a few different ways.
Databases and Data Lakes
Databases were popularized in the 1980s. Sure, they were originated way before, but a relational database came into the spotlight in the 80s.
Databases are set up for monitoring and updating the real-time structured data. However, have can withhold just the most recent data available.
By default, databases are highly structured.
Let’s understand by calling a common database as a repository of information that is extracted and derived from a series of sources. This information is then stored in specific formats under different files and folders.
One thing worth noting is that the compatibility of such information with all the other programs and clients involves restructuring the data to a different format. However, this isn?t a hard and fast rule. It happens in a few scenarios.
As such, databases commonly move slower than data lakes. Another common problem is that the storage costs could relatively be higher since the uptime of databases is considered important and they can?t face uptime issues.
On the other hand, data lakes store all the necessary data in their raw and unstructured formats which makes us realize that data lakes rely on the structural markers. These include filetypes as well.
A data lake also provides data that is eligible to transport between processes and could be read by a variety of programs. However, as compared to databases, storage costs for such type of data management setup are lower.
However, the important thing is that the data structure and requirements aren?t defined up until the data is needed for some purpose.
Data lakes could involve the use of a variety of storage and processing tools for the sake of extracting value as soon as possible and inform the key organizational decisions.
Future of these technologies (and is data lake a database?)
Let’s be honest here. If you think that technologies like data lakes, data warehouses, and databases are likely to overtake one another, you’re wrong!
Because as the value and volume of the unstructured data are rushing, data lakes are going to become more popular and widely adopted technologies. But that doesn’t mean databases are going to be forgotten about in the scenario.
You are most likely going to continue to keep all your structured data in your database rather than trusting a different method of data storage. Why? Because it’s convenient. Companies now are efficiently moving all their unstructured data to data lakes on the cloud. This is a common scenario in today’s technological era where we are moving towards cost-effective solutions and making the transportation of data more feasible.
The workload that involves these databases and data lakes in all the different cases is one that works well. This is most likely going to be continued in the future.?
Now, to our main question – is data lake a database?
The reason for the denial is because both these technologies are focusing on establishing a good working ground for smaller businesses and helping them lower the barrier of entry.
With the different widespread adoption, they receive, it is more likely to become more convenient to invest in both these types of data storages since both of these perform different functions.
While some of the features of these technologies do align, they are certainly different when it comes to functionality and it would be safe to assume to consider data lakes as relational databases.