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Optimizing data warehouse storage

The Netflix TechBlog

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 208
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Designing Instagram

High Scalability

Firstly, the synchronous process which is responsible for uploading image content on file storage, persisting the media metadata in graph data-storage, returning the confirmation message to the user and triggering the process to update the user activity. Some of the keys of understanding the user network are listed below.

Design 334
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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

These include challenges with tail latency and idempotency, managing “wide” partitions with many rows, handling single large “fat” columns, and slow response pagination. It also serves as central configuration of access patterns such as consistency or latency targets. Useful for keeping “n-newest” or prefix path deletion.

Latency 256
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Reducing Your Database Hosting Costs: DigitalOcean vs. AWS vs. Azure

Scalegrid

Since database hosting is more dependent on memory (RAM) than storage, we are going to compare various instance sizes ranging from just 1GB of RAM up to 64GB of RAM so you can see how costs vary across different application workloads. Does it affect latency? Yes, you can see an increase in latency. EC2 instances. VM instances.

Azure 344
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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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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. Bandwidth optimization: Caching reduces the amount of data transferred over the network, minimizing bandwidth usage and improving efficiency.

Cache 246
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Dynatrace Managed turnkey Premium High Availability for globally distributed data centers (Early Adopter)

Dynatrace

The network latency between cluster nodes should be around 10 ms or less. Minimized cross-data center network traffic. For Premium HA, this has been extended from 10 ms latency (in the same network region) to around 100 ms network latency due to asynchronous data replication between regions.