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Article: Magic Pocket: Dropbox’s Exabyte-Scale Blob Storage System

InfoQ

A horizontally scalable exabyte-scale blob storage system which operates out of multiple regions, Magic Pocket is used to store all of Dropbox’s data. Adopting SMR technology and erasure codes, the system has extremely high durability guarantees but is cheaper than operating in the cloud. By Facundo Agriel

Storage 109
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Improved Alerting with Atlas Streaming Eval

The Netflix TechBlog

Ruchir Jha , Brian Harrington , Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. It opens doors to support more exciting use-cases.

Storage 288
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Google Improves Cloud Spanner: More Compute and Storage without Price Increase

InfoQ

Google recently announced various improvements to Cloud Spanner, its distributed, decoupled relational database service with a “50% increase in throughput and 2.5 times the storage per node than before” without a price change. By Steef-Jan Wiggers

Google 98
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DBaaS Pros & Cons

Scalegrid

In today’s rapidly evolving digital landscape, the way we manage databases is undergoing a transformative shift. The rise of Database-as-a-Service (DBaaS) is not just a trend but a strategic response to the growing complexities of data management. However, using a database as a service is not without its set of challenges.

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Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs

InfoQ

Zendesk reduced its data storage costs by over 80% by migrating from DynamoDB to a tiered storage solution using MySQL and S3. The company considered different storage technologies and decided to combine the relational database and the object store to strike a balance between querybility and scalability while keeping the costs down.

Storage 132
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Designing Instagram

High Scalability

Currently, he is in the Alexa Shopping organization where he is developing machine-learning-based solutions to send personalized reorder hints to customers for improving their experience. We will use a graph database such as Neo4j to store the information. Problem Statement. System Components. Component Design. Posting on Instagram.

Design 334
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Optimize your environment: Unveiling Dynatrace Hyper-V extension for enhanced performance and efficient troubleshooting

Dynatrace

Secondly, determining the correct allocation of resources (CPU, memory, storage) to each virtual machine to ensure optimal performance without over-provisioning can be difficult. We’ve worked with our partners and customers to internalize the Hyper-V observability practices they have developed over years of experience running Hyper-V.