In this thesis we present the concepts of data lakes and big data. With
the help of the opensource data storage solution MinIO we setup our own
data lake. We take a detailed look at MinIO and showcase its strengths and
weaknesses. We also take a look at other data storage solutions like LakeFS,
Ceph, Hadoop and AWS and compare them with MinIO.
We deploy our data lake into a working environment where we evaluate
it from the perspective of an independent user. We compare three diff erent
scenarios of using MinIO and track transfer speeds for each of them. We
also explore the scalability options MinIO off ers and assess the complexity
of setting up our custom data lake.
We analize the processes of fi lling, retrieving and tagging the data in our
MinIO data lake. We fi nd that MinIO is easy to use, as it can be used
in multiple environments and has a detailed documentation on its offi cial
website. We conclude that MinIO is an eff ective tool for a user working with
large quantities of diff erent types of data.
|
