How Apache Pinot Compares to Database Alternatives
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- เผยแพร่เมื่อ 21 ต.ค. 2024
- Join: stree.ai/slack | Sub: stree.ai/sub | Join Tim Berglund (VP of Developer Relations) as he explores the unique capabilities of Apache Pinot in the realm of real-time analytics databases. In this insightful video, Tim delves into the nuances of various database technologies like key-value stores, search technologies, and data warehouses, comparing them with Pinot across several dimensions such as data freshness, query latency, throughput, and flexibility.
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This is great Tim. I think you should have added the 5th category which are lake engines. Trino, Spark,etc.. higher latency, joins, large queries,etc..
Though it must be said that Trino + Pinot is a *great* combo.
It would be great if there is a cost calculator between those 4 options with few basic inputs like users, data volume, velocity etc. Another concern is ability to find resources.
Hey! It would be great to see how it compares to in-memory data grids (GridGain/Ignite, Gemfire/Geode, Coherence) that provide some SQL-ish capabilities and are still commonly used for similar cases - muliti-QPS realtime analytics.
could I use Pinot for traditional DWH workloads as well?
Did they get a reverse printed tree specifically for this video!?