B‑Tree vs LSM‑Tree: Which Storage Engine Fits Your Database Workload?

This article examines the fundamental differences between B‑Tree and LSM‑Tree storage structures in distributed and relational databases, detailing their write and read paths, performance trade‑offs, update handling, lock conflicts, and high‑availability considerations to help engineers choose the right engine for their workloads.

B-TreeDatabase StorageLSM‑Tree

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B‑Tree vs LSM‑Tree: Which Storage Engine Fits Your Database Workload?

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Sep 25, 2022 · Databases

Boost Large Table Queries with Query Separation: Strategies, Implementation, and Storage Choices

Query separation stores a copy of data in a dedicated query system to accelerate large‑table reads, addressing cold‑data latency, write limitations, and scalability, with detailed guidance on when to adopt it, implementation methods (sync, async, binlog), storage options, MQ handling, and consistency considerations.

Large TablesRead Performancequery separation

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Boost Large Table Queries with Query Separation: Strategies, Implementation, and Storage Choices