Remove Benchmarking Remove Design Remove Example Remove Latency
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MySQL on Azure Performance Benchmark – ScaleGrid vs. Azure Database

Scalegrid

ScaleGrid MySQL on Azure so you can see which provider offers the best throughput and latency performance. We measure latency in ms 95th percentile latency. During Read-Intensive Workloads, ScaleGrid manages to achieve up to 3 times higher throughput and averages 66% better latency compared to Azure Database.

Azure 299
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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

An application example is a session store recording recent actions. We note that for MongoDB update latency is really very low (low is better) compared to other dbs, however the read latency is on the higher side. Application example: photo tagging; add a tag is an update, but most operations are to read tags. Conclusion.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130
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Why you should benchmark your database using stored procedures

HammerDB

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. HammerDB has always used stored procedures as a design decision because the original benchmark was implemented as close as possible to the example workload in the TPC-C specification that uses stored procedures.

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Netflix at AWS re:Invent 2019

The Netflix TechBlog

This entertaining romp through the tech stack serves as an introduction to how we think about and design systems, the Netflix approach to operational challenges, and how other organizations can apply our thought processes and technologies. In order to maintain performance, benchmarking is a vital part of our system’s lifecycle.

AWS 100
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

This entertaining romp through the tech stack serves as an introduction to how we think about and design systems, the Netflix approach to operational challenges, and how other organizations can apply our thought processes and technologies. In order to maintain performance, benchmarking is a vital part of our system’s lifecycle.

AWS 100
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

a Netflix member via Twitter This is an example of a question our on-call engineers need to answer to help resolve a member issue?—?which Now let’s look at how we designed the tracing infrastructure that powers Edgar. which is difficult when troubleshooting distributed systems.