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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., All of these dbs are available free of cost for download / install and it will be fairly straightforward to run these tests in your environment for further analysis. Workload C: Read only. This workload is 100% read. Conclusion.

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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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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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The Ultimate Guide to Database High Availability

Percona

To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. This guide provides an overview of what high availability means, the components involved, how to measure high availability, and how to achieve it. How does high availability work?

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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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PostgreSQL: Pgpool-II Use Cases and Benefits

Percona

Query caching Pgpool-II can cache frequently used queries in memory, reducing the load on your PostgreSQL servers and improving response times. This means that when a query is executed, pgpool-II can check the cache first to see if the results are already available rather than sending the query to the database server.

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