Challenges with data lakes
There are some challenges with a data lake. Some are:-
- Hard to append data
Adding newly arrived data leads to incorrect reads
2. Modification of exiting data is difficult
GDPR/CCPA requires making fine-grained changes to exiting the data lake.
3. Jobs failing mid way
Half of the data appears in the data lake, the rest is missing.
4. Real-time operations
Mixing streaming and batch leads to inconsistency.
5. Costly to keep historical versions of the data.
Regulated environments require reproductivity, auditing, governance.
6. Difficult to handle large metadata
For large data lakes, the metadata itself becomes difficult to manage.
7. Too many files problems
Data lakes are not great at handling millions of small files
8. Hard to get great performance
Partitioning the data for performance is error-prone and difficult to change.
9. Data quality issue
It's a constant headache to ensure that all the data is correct and of high quality.
Note: In case you notice any errata in my understanding, feel free to reach out and let me know of the same and I will update the blog post accordingly.