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A one size fits all database doesn't fit anyone

All Things Distributed

A common question that I get is why do we offer so many database products? To do this, they need to be able to use multiple databases and data models within the same application. Seldom can one database fit the needs of multiple distinct use cases. Seldom can one database fit the needs of multiple distinct use cases.

Database 167
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Cloudburst: stateful functions-as-a-service

The Morning Paper

Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).

Lambda 98
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Percentiles don’t work: Analyzing the distribution of response times for web services

Adrian Cockcroft

> system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, Changes in behavior of the system from minute to minute is going to change the height of each peak, as the workload mix and cache hit rates change.

Lambda 98
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Fast key-value stores: an idea whose time has come and gone

The Morning Paper

Coupled with stateless application servers to execute business logic and a database-like system to provide persistent storage, they form a core component of popular data center service archictectures. The network latency of fetching data over the network, even considering fast data center networks. Oh, you mean a cache?

Cache 79
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Accelerating Data: Faster and More Scalable ElastiCache for Redis

All Things Distributed

Fast Data is an emerging industry term for information that is arriving at high volume and incredible rates, faster than traditional databases can manage. While caching continues to be a dominant use of ElastiCache for Redis, we see customers increasingly use it as an in-memory NoSQL database. Redis and Fast Data.

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Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

Which I’m quite happy to see as my most recent data pipeline is based around Lambda, S3, and Athena, and it’s been working great for my use case. For query executors that can be frequently started and stopped the authors explore performance with cold and warm caches (where applicable), and also the horizontal and vertical scaling performance.

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Optimizing CDN Management Using Terraform

IO River

It’s not just limited to cloud resources like AWS and Azure; Terraform is versatile, extending its capabilities to key performance areas like Content Delivery Network (CDN) management, ensuring efficient content delivery and optimal user experience.‍Started This level of granularity is not found in UI-managed systems.Â