This article benchmarks four MySQL stored functions to show how unreachable (dead) code inside functions, procedures, and triggers inflates execution time, visualizes their system calls with performance_schema, and explains the resulting memory and trigger performance impacts.
This article introduces Java Microbenchmark Harness (JMH), explains why precise benchmarking matters, and walks through twelve typical testing pitfalls—such as dead‑code elimination, constant folding, loop misuse, fork isolation, method inlining, false sharing, branch prediction, and multithreading—showing how JMH helps developers obtain reliable performance measurements.
A Chinese company, StarRing Technology, became the first ever to pass the notoriously difficult TPC‑DS benchmark, revealing the test’s history, methodology, and why this achievement marks a major milestone for database performance in the big‑data era.
At QCon 2018 in Beijing, Suning’s Silicon Valley Research Institute showcased its cutting‑edge facial‑recognition system—leveraging ResNet and Inception‑ResNet architectures—to achieve top global rankings and enable real‑time, contact‑less services such as unmanned stores, employee access control, and intelligent store video analytics.
The article analyzes why Go's ioutil.ReadAll becomes a performance bottleneck in IO‑intensive workloads after CPU microcode patches, explains the underlying buffer reallocations, and presents a multi‑level memory‑pool design that reduces allocations and achieves roughly a 19‑fold speedup.
This article explains the concept of asynchronous I/O, introduces Python’s provisional asyncio module, and walks through a complete example that creates an HTTP keep‑alive benchmark tool, including code, test environment, performance results, and key asyncio concepts such as event loops, futures, coroutines, and generators.
This article evaluates popular front‑end frameworks by measuring real‑world performance, bundle size, and source‑code line counts using a medium‑scale blog project, providing practical insights to help developers choose the most suitable framework for their applications.
Through a series of Gradle‑based benchmarks on clean, daemon‑enabled, and incremental builds, this study compares Java and Kotlin compilation times, revealing that while Java is slightly faster on cold builds, Kotlin matches or exceeds Java in typical incremental scenarios.
This article explains Vim’s powerful, extensible features, presents benchmark comparisons of memory consumption and operation speed against editors like Emacs, Nano, VS Code, Atom, Sublime, and shows why many developers still prefer Vim for efficient text editing.
The Intel 545S SSD, featuring a 64‑layer TLC 3D NAND architecture, is evaluated through extensive synthetic and real‑world benchmarks, revealing solid sequential speeds, decent read latency, but notable firmware stability issues that currently limit its recommendation despite an attractive price point.
The article examines why the author favors React for server‑side rendering despite the rise of lightweight libraries like Preact and Inferno, discussing checksum handling, compatibility, maintainability, future roadmap, and presenting benchmark data that shows React@16’s performance gains.
This article translates and expands on Mark Callaghan’s sysbench benchmark, revealing that MySQL 5.6‑5.7 suffers the steepest QPS drop in low‑concurrency tests, compares configurations across versions, presents detailed charts, and concludes that most performance regressions are isolated to the 5.7 release.
This article explains Kafka's distributed architecture, its topic‑partition storage model, replication and synchronization mechanisms, reliability guarantees such as ISR and high‑watermark, and presents benchmark results that illustrate how replication factor, acks settings, and partition count affect throughput and latency.
This article explains how to evaluate SSD performance by processing raw fio benchmark logs, interpreting bandwidth, IOPS, and latency metrics, converting logs to CSV, visualizing results with charts, and drawing practical conclusions for storage selection and reliability.
This article explains how to evaluate SSD performance by detailing the benchmark environment, required hardware, preferred testing tools like fio, essential disk requirements, common pitfalls, and a comprehensive set of test items and scripts for both raw disks and typical filesystems.
This article presents a comprehensive Java benchmark that compares JSON libraries (Jackson, Fastjson, DSL‑JSON, Jsoniter, Thrift) with Google Protocol Buffers across various data types and structures, revealing where Protobuf truly outperforms JSON and where modern JSON parsers narrow the gap.
This article explains the key SSD benchmark indicators—4K random I/O, sustained throughput, performance consistency, durability, and write amplification—while describing why they matter for evaluating storage solutions and guiding proper SSD selection for production workloads.
This article recounts the Huajiao team's migration from PHP 5 to PHP 7, detailing the motivations, upgrade hurdles, extensive performance benchmarks, gray‑release strategy, and operational steps that together delivered up to 30% CPU savings and significant cost reductions.
This article benchmarks Java JSON libraries against Google Protobuf, analyzing decode/encode performance for integers, doubles, strings, objects, and lists, revealing that while Protobuf often outperforms JSON, optimized JSON libraries like DSL‑JSON can narrow the gap dramatically.
The benchmark shows that while InnoDB delivers roughly 30 % higher insert throughput than TokuDB, the TokuDB engine achieves 10‑16× storage compression with comparable import times, minimal impact from log‑sync settings, and zlib emerging as the preferred compression algorithm for balanced performance and CPU usage.
This article presents a detailed benchmark comparing PostgreSQL 9.6 and MySQL 5.7 on identical high‑end hardware using pgbench and SysBench, describing the test methodology, configuration tweaks, performance results for point selects and OLTP workloads, and concluding that both systems scale to modern demanding workloads.
The article summarizes the SPEC 2016 Asian Summit, explains SPEC's role in defining server and cloud performance benchmarks—including CPU, web, and file‑system tests—and highlights the introduction of the SPEC Cloud IaaS 2016 benchmark for evaluating cloud infrastructure performance.
This article benchmarks four widely used RPC frameworks—Dubbo, Motan, rpcx, gRPC, and Thrift—by measuring throughput, average latency, median latency, and maximum latency under varying client concurrency levels, revealing rpcx’s superior performance and the impact of serialization choices.
This article explains how to use MySQL's built‑in mysqlslap tool to benchmark database performance, covering basic commands, adding concurrency, generating complex tables, and testing with custom schemas and queries, while interpreting the resulting metrics for optimization decisions.
A benchmark on a test server comparing Redis and SSDB using one million SET, GET, HSET, and HGET requests with 1,000 concurrent clients shows SSDB delivering far lower QPS than Redis, contradicting the performance figures advertised by SSDB.
This article presents a comprehensive Kafka benchmark using six machines to evaluate producer and consumer throughput, replication effects, message size impact, and end‑to‑end latency, providing detailed results, analysis, and reproducible test commands.
This article outlines ten practical guidelines—ranging from test environment consistency and dedicated hardware to network capacity checks, OS tuning, realistic workloads, proper test duration, and comprehensive result reporting—to ensure reliable and reproducible HTTP server performance benchmarks.
A benchmark using ApacheBench compares Nginx static serving, a Golang HTTP server, and a PHP7+Swoole server under 100‑concurrent connections for one million requests, showing PHP7+Swoole achieving roughly 75 % higher QPS than both Nginx and Golang, along with detailed environment, code, and resource usage data.
This article presents comprehensive MongoDB performance benchmarks, discusses version-specific issues, and offers practical best‑practice recommendations for schema design, driver usage, replication, and monitoring to help engineers optimize their deployments.
This guide explains how to install and use the lightweight Linux tool http_load to benchmark web server performance, covering preparation of URL lists, key command‑line parameters, example test runs, and interpretation of the detailed output statistics.
This article benchmarks three JavaScript techniques for updating a div's content—direct innerHTML concatenation, building a string before assignment, and assigning a pre‑built string—showing their execution times and explaining why minimizing DOM modifications dramatically improves performance.
The article recounts a hands‑on K‑DB experience event where participants migrated Oracle workloads, benchmarked K‑DB against Oracle using TPMC, explored the K‑RAC cluster feature, and shared detailed observations that highlight K‑DB's compatibility, performance, and stability in a real‑world setting.
This article reviews the evolution of big‑data management technologies, discusses the criteria for choosing appropriate big‑data benchmarks, compares existing benchmarks such as MapReduce tests, YCSB, BigBench and BigFrame, and provides an in‑depth analysis of the TPC‑DS benchmark and its certification status.
The article explains MySQL Cluster as a real‑time, ACID‑compliant, in‑memory distributed database, describes its node architecture, transparent sharding for linear scalability, various SQL/NoSQL access methods, and presents a benchmark achieving 200 million queries per second on 32 data nodes.
This article introduces MySQL Cluster, an in‑memory, real‑time, ACID‑compliant distributed database, explains its multi‑master architecture, data, application and management nodes, transparent partitioning, NoSQL APIs, and presents a benchmark achieving 200 million queries per second on up to 32 nodes.
This guide explains how to use Redis's built‑in redis-benchmark tool to measure the throughput of local or remote Redis instances, covering basic testing, selective command benchmarking, and remote server testing with practical command examples.
