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Why you should benchmark your database using stored procedures

HammerDB

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. HammerDB has always used stored procedures as a design decision because the original benchmark was implemented as close as possible to the example workload in the TPC-C specification that uses stored procedures. On MySQL, we saw a 1.5X

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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

About the cluster Following a step-by-step process, the objective is to create a four-node cluster consisting of: PostgreSQL version 15 Citus extension (I’ll be using version 11, but there are newer ones available.) In order to speed up the benchmark indexes must be added. psql pgbench <<_eof1_ qecho adding node citus3.

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How to maximize CPU performance for PostgreSQL 12.0 benchmarks on Linux

HammerDB

HammerDB doesn’t publish competitive database benchmarks, instead we always encourage people to be better informed by running their own. So over at Phoronix some database benchmarks were published showing PostgreSQL 12 Performance With AMD EPYC 7742 vs. Intel Xeon Platinum 8280 Benchmarks . uname -a Linux ubuntu19 5.3.0-rc3-custom

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10 tips for migrating from monolith to microservices

Dynatrace

Limits of a lift-and-shift approach A traditional lift-and-shift approach, where teams migrate a monolithic application directly onto hardware hosted in the cloud, may seem like the logical first step toward application transformation. remove the dependency on the monolith after all testing is successful. create a microservice; 2.

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Faster remainders when the divisor is a constant: beating compilers and libdivide

Daniel Lemire

The division by a power of two ( / (2 N )) can be implemented as a right shift if we are working with unsigned integers, which compiles to single instruction: that is possible because the underlying hardware uses a base 2. The computation of the remainder is nice, but I really like better the divisibility test. It tells a nice story.

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The top 5 reasons to run your own database benchmarks

HammerDB

Some opinions claim that “Benchmarks are meaningless”, “benchmarks are irrelevant” or “benchmarks are nothing like your real applications” However for others “Benchmarks matter,” as they “account for the processing architecture and speed, memory, storage subsystems and the database engine.”

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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. This plays a crucial role in supervising the replication process.

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