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Redis on Azure Performance Benchmark – ScaleGrid for Redis™ vs. Azure Cache

Scalegrid

Redis is a great caching solution for highly demanding applications, and there are […]. In fact, it is the number one key value store and eighth most popular database in the world. It has high throughput and runs from memory, but also has the ability to persist data on disk.

Cache 130
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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

Application example: user profile cache, where profiles are constructed elsewhere (e.g., Here Redis and Yugabyte have higher latencies, Yugabyte performs bad for both Insert and Read for the test. Yugabyte performs really good in this test. Workload C: Read only. This workload is 100% read. Workload E: Short ranges. Conclusion.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Redis® is an in-memory database that provides blazingly fast performance. This makes it a compelling alternative to disk-based databases when performance is a concern. You might already use ScaleGrid hosting for Redis hosting to power your performance-sensitive applications.

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Redis vs Memcached in 2024

Scalegrid

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis and Memcached both provide high performance with sub-millisecond response times. Choosing between Redis and Memcached hinges on specific application requirements.

Cache 130
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Why Tcl is 700% faster than Python for database benchmarking

HammerDB

Python is a popular programming language, especially for beginners, and consequently we see it occurring in places where it just shouldn’t be used, such as database benchmarking. We use stored procedures because, as the introductory post shows, using single SQL statements turns our database benchmark into a network test).

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How to Assess MySQL Performance

HammerDB

Predicting application performance is a difficult art, but an important one when choosing the target deployment environment. In this blog, we aim to call out some key considerations when trying to assess MySQL performance for your application. We will not concern ourselves with the raw throughput of workload.

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Measure What You Impact, Not What You Influence

CSS Wizardry

A thing I see developers do time and time again is make performance-facing changes to their sites and apps, but mistakes in how they measure them often lead to incorrect conclusions about the effectiveness of that work. Problems When Measuring Performance. For example, continuing our task to reduce CSS size: performance.