Oracle Data Lake Offerings – A Quiver Full of Arrows

“Data Lake” term has now blended in the daily discussion of every customer in such a way that without which analytical solution seems incomplete. It makes sense also to build a data lake from obvious reason to store all relevant data as well as appear to be irrelevant data today that may become relevant tomorrow. I will not go into details of “necessity vs desire” types of discussion but I would like to highlight that almost every OEM in data lake technology has product offerings. These products are something like different types of arrows kept in the quiver, which are essential in different type of situations.

In the same context, Oracle is no exception to this. Being a global leader in the data technologies arena, it becomes inevitable for Oracle to invest in the development of data lake technology related components so that customer could take advantage on using them on Oracle Platform either On-premise or in the Cloud.

The below table basically represents all the aspects of data lake i.e. Data Integration & Data Processing, Data Repository & Data Management, Data Analysis & Visualization.

Now a days, cloud is another area of focus among the organizations and developers. The rich portfolio of PaaS services are in demand across the cloud server providers (CSPs) especially in the data lake development. I will not go into details of these products one by one that what Oracle has in the offerings, but I can vouch that all these products are sufficient to build a data lake solution including data warehousing solution for almost all of the Industries, Domain or business requirements. Let me also present an another look of these tools by comparing them with market leaders in the cloud space, just to give you a glimpse of what Oracle is holding in its platform.

Just a disclaimer, I might be wrong in categorizing some of the PaaS services, but I have tried to best of my knowledge and understandings. In this table, you will see, Oracle being addressing almost every aspect of what data lake development requires. I hope this will help you to compare the products and go through them in detail of each component.