Demystifying Real-time Analytics, Search and Hybrid Search with Dhruba, CTO @Rockset 

In this video, I talk to Dhruba, CTO @Rockset about search and realtime analytics. We discussed deep internals of Rockset, its architecture and why is it a great fit for search and realtime analytics use cases.
Chapters:
00:00 Introduction
02:45 The Evolution of Data Systems: From Hadoop to Rockset
07:30 Understanding Rockset: Real-Time Analytics and Search Defined
12:01 The Technical Edge: Rockset vs. Elasticsearch
18:16 Deep Dive into Rockset's Architecture and Internals
28:21 Partitioning, Hashing, and Data Distribution in Rockset
36:56 Exploring Hot Storage and Cache Layers
37:40 Why Hot Storage is Essential for Low Latency
39:05 Optimizing Data Storage with Compression and Delta Encoding
39:49 Balancing Cost and Performance in Data Storage
41:50 The Power of Converged Indexing in Rockset
45:50 Efficient Query Execution and Index Management
54:51 Leveraging Mutability for Real-Time Analytics
59:24 Deep Dive into Query Processing and Optimization
01:04:21 Understanding Joins and Reporting Queries in Rockset
01:12:23 Future Directions and Vector Search Innovations
Index Conference: rockset.com/index-conf/
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