Welcome to Cloud Forward. In this series, we will dive deep into the basics and featured of PolarDB
The need for more reads and fewer writes places enormous pressure on the database's read capacity. To solve this issue, here comes the R/W splitting.
Strict Consistency Cluster was introduced to PolarDB to solve inconsistency issues caused by delayed reading from RO nodes.
For faster R/W speeds, the scaling bottleneck of "one-writer, many readers" for relational databases must be overcome, and Multi-Master might just be the key to it.
HTAP can help cut down your O&M, and PolarDB's In-Memory Column Index feature allows you to meet OLTP and OLAP requirements with one system.
To truly resolve the issue of SQL execution time getting slower as data gets bigger, PolarDB for MySQL adopted the feature of Parallel Query at the kernel level.
Cross-Region R/W Latency between applications and databases is crucial especially when you are running a global business.
In this episode, we will dive deep into the search for a database that is as elastic and scalable as cloud computing.
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