Remove Cache Remove Efficiency Remove Storage
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The Power of Caching: Boosting API Performance and Scalability

DZone

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing.

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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

Our goal was to build a versatile and efficient data storage solution that could handle a wide variety of use cases, ranging from the simplest hashmaps to more complex data structures, all while ensuring high availability, tunable consistency, and low latency. Developers just provide their data problem rather than a database solution!

Latency 256
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MySQL Data Caching Efficiency

Percona

A shared characteristic in most (if not all) databases, be them traditional relational databases like Oracle, MySQL, and PostgreSQL or some kind of NoSQL-style database like MongoDB, is the use of a caching mechanism to keep (a copy of) part of the data in memory. How do you know if your MySQL database caching is operating efficiently?

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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

Figure 1: A Simplified Video Processing Pipeline With this architecture, chunk encoding is very efficient and processed in distributed cloud computing instances. From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step.

Cloud 240
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AWS serverless services: Exploring your options

Dynatrace

This means you no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Speed is next; serverless solutions are quick to spin up or down as needed, and there are no delays due to limited storage or resource access. AWS offers four serverless offerings for storage.

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Dynatrace Kubernetes Observability for Persistent Volume Claims

Dynatrace

Interestingly, our partner RedHat reported in 2021 that around 80% of deployed workloads are databases or data caches, storing data in persistent volume claims (PVCs). You quickly realize that it will take ages to fill up the overprovisioned database storage. Two days later, your database runs out of storage in the middle of the night.

Storage 246
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Mastering Disk Space Management with MongoDB® Storage Engines

Scalegrid

MongoDB offers several storage engines that cater to various use cases. The default storage engine in earlier versions was MMAPv1, which utilized memory-mapped files and document-level locking. The newer, pluggable storage engine, WiredTiger, addresses this by using prefix compression, collection-level locking, and row-based storage.

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