A new turn in building analytics on embedded databases
summary
The talk explains how embedded databases can replace heavy DWH and OLAP systems to reduce complexity, resource use, and cost. It covers practical approaches and examples of building analytics directly on embedded database technologies to solve common data-warehousing problems.
AI-written summary · about
chapters (7)
- 0:00Introduction
- 3:21Data storage evolution
- 10:04What is H-computing
- 13:10Crypto exchange case
- 25:22OLTP and storage
- 28:08Summary and trends
- 30:38Q&A
related talks
05mThe Future of Data Warehousing
58mUnderstanding Big Data for Software Engineers
07mIn-Hadoop Analytics: Bringing analytics to big data
31mData Unleashed: A Developer's Perspective on Navigating the Architecture Maze
31mData Warehouses Meet Data Lakes
28mRelational Databases Don't call it a comeback!
01h 01mModern Data Warehousing Strategy
56mData Unleashed: A Developer's Perspective on Navigating the Architecture Maze
