What is Data Management and Why Is It Required?
Why Hybrid Data Management?
To understand hybrid data management better, it is important to understand the differences between traditional and emerging data & analytics platforms.Feature | Traditional | Emerging |
---|---|---|
Infrastructure | On Premises | Cloud |
Data Format | Structured | Unstructured |
Database | RDBMS | No SQL, Open Source |
Data Platform | Data warehouse | Data Lake |
Data Management Software (ETL, Reporting, Visualization, Advanced Analytics) | Commodity Software | Open Source |
Feature | Traditional | Emerging |
---|---|---|
Cost | Startup costs are higher and ongoing costs may be lower | Startup costs are lower and ongoing costs will be higher (OPEX) |
Time to start | Can start late as per budget available | Need to start fast to maximize ROI |
Disaster Recovery (DR) | DR can be additional cost | Mostly built-in DR capability |
Scalability | Not Adequate. Scalability at additional cost and time | Flexibility to scale with business needs. However, if not planned accurately, cloud fees can add up quickly |
Data Security | Complete control of | Confidentiality control based on cloud vendor |
highly confidential information | ||
data privacy | ||
infrastructure risks & outages | ||
Technical Community | Limited quantity of subject matter experts | Open Source community is growing with quicker turnaround for issues and challenges |