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Best MySQL DigitalOcean Performance – ScaleGrid vs. DigitalOcean Managed Databases

Scalegrid

Compare Latency. On average, ScaleGrid achieves almost 30% lower latency over DigitalOcean for the same deployment configurations. MySQL DigitalOcean Performance Benchmark. In this benchmark, we compare equivalent plan sizes between ScaleGrid MySQL on DigitalOcean and DigitalOcean Managed Databases for MySQL. Throughput.

Database 217
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Comparing PostgreSQL DigitalOcean Performance & Pricing – ScaleGrid vs. DigitalOcean Managed Databases

Scalegrid

Compare Latency. lower latency compared to DigitalOcean for PostgreSQL. Now, let’s take a look at the throughput and latency performance of our comparison. Next, we are going to test and compare the latency performance between ScaleGrid and DigitalOcean for PostgreSQL. PostgreSQL DigitalOcean Latency Averages (ms).

Database 230
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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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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

Leveraging pgbench , which is a benchmarking utility that comes bundled with PostgreSQL, I will put the cluster through its paces by executing a series of DML operations. And now, execute the benchmark: -- execute the following on the coordinator node pgbench -c 20 -j 3 -T 60 -P 3 pgbench The results are not pretty.

Database 105
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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

While there is no magic bullet for MySQL performance tuning, there are a few areas that can be focused on upfront that can dramatically improve the performance of your MySQL installation. What are the Benefits of MySQL Performance Tuning? A finely tuned database processes queries more efficiently, leading to swifter results.

Tuning 52
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The evolution of single-core bandwidth in multicore processors

John McCalpin

I have a lot of historical data using my ReadOnly benchmark (as described in some of the earliest entries in this blog [link] A read-only access pattern removes the need to understand and explain the many complexities associated with the “streaming stores” typically used in the STREAM benchmark (e.g., Stay tuned!

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Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

A co-worker introduced me to Craig Hanson and Pat Crain's performance mantras, which neatly summarize much of what we do in performance analysis and tuning. These have inspired me to summarize another performance activity: evaluating benchmark accuracy. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?