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

High Scalability

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. The latency table shows that 99th percentile latency for Yugabyte is quite high compared to others (lower is better). Again Yugabyte latency is quite high. 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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Redis vs Memcached in 2024

Scalegrid

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130
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5.5 mm in 1.25 nanoseconds

Randon ASCII

That meant I started having regular meetings with the hardware engineers who were working with IBM on the CPU which gave me even more expertise on this CPU, which was critical in helping me discover a design flaw in one of its instructions , and in helping game developers master this finicky beast. To the left of that is one of the CPU cores.

Cache 126
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The evolution of single-core bandwidth in multicore processors

John McCalpin

For most high-end processors these values have remained in the range of 75% to 85% of the peak DRAM bandwidth of the system over the past 15-20 years — an amazing accomplishment given the increase in core count (with its associated cache coherence issues), number of DRAM channels, and ever-increasing pipelining of the DRAMs themselves.

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Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook

The Morning Paper

Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook , Cao et al., Or in the case of key-value stores, what you benchmark. So if you want to design a system that will offer good real-world performance, it’s really useful to have benchmarks that accurately represent real-world workloads.

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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

Here’s some predictions I’m making: Jack Dongarra’s efforts to highlight the low efficiency of the HPCG benchmark as an issue will influence the next generation of supercomputer architectures to optimize for sparse matrix computations. In early January a related paper was published by Satoshi Matsuoka et. petaflops, which is 0.8%