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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., The latency table shows that 99th percentile latency for Yugabyte is quite high compared to others (lower is better). Workload C: Read only. This workload is 100% read. However, Very high Read latency for MonoDB makes it the last db to finish the task.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. offers the Software Watchdog specifically designed for this purpose.

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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.

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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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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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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.

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