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Compression Methods in MongoDB: Snappy vs. Zstd

Percona

Compression in any database is necessary as it has many advantages, like storage reduction, data transmission time, etc. Storage reduction alone results in significant cost savings, and we can save more data in the same space. By default, MongoDB provides a snappy block compression method for storage and network communication.

Storage 111
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Maximizing Performance of AWS RDS for MySQL with Dedicated Log Volumes

Percona

A Dedicated Log Volume (DLV) is a specialized storage volume designed to house database transaction logs separately from the volume containing the database tables. This separation aims to streamline transaction write logging, improving efficiency and consistency. Who can benefit from DLV? and later v10 versions MySQL: 8.0.28

AWS 99
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MongoDB Rollback: How to Minimize Data Loss

Scalegrid

Data-bearing members face a higher risk of encountering issues caused by rollbacks, compared to others who utilize different storage methods. By incorporating journaling into MongoDB, data integrity is maintained while reducing latency for writing, ultimately improving the overall stability and performance of the database.

Database 130
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MongoDB Best Practices: Security, Data Modeling, & Schema Design

Percona

The CFQ works well for many general use cases but lacks latency guarantees. The deadline excels at latency-sensitive use cases ( like databases ), and noop is closer to no schedule at all. On the other hand, MongoDB schema design takes a document-oriented approach. Two other schedulers are deadline and noop.

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Five Data-Loading Patterns To Improve Frontend Performance

Smashing Magazine

Jamstack is popular with documentation sites that usually compile code to HTML files and host them on the CDN. Caching partially stores your data and is not used as permanent storage. Using the cache as permanent storage is an anti-pattern. Both can be used simultaneously but will ultimately serve a different purpose.

Cache 125
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Proof of Concept: Horizontal Write Scaling for MySQL With Kubernetes Operator

Percona

This operation is quite expensive but our database can run it in a few milliseconds or less, thanks to several optimizations that allow the node to execute most of them in memory with no or little access to mass storage. The key factor is that the whole data structure resides in the same location (node), facilitating the operations.

Traffic 125
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Who monitors the monitoring systems?

Adrian Cockcroft

Juvenal Photo taken in Lisbon Portugal by Adrian Cockcroft The documentation for most monitoring tools describes how to use that tool in isolation, often as if no other tools exist, but sometimes with ways to import or export some of the data to other tools. “Quis custodiet ipsos custodes?”?—?Juvenal