Remove Benchmarking Remove Hardware Remove Traffic
article thumbnail

RabbitMQ vs. Kafka: Key Differences

Scalegrid

However, performance can decline under high traffic conditions. Several factors impact RabbitMQs responsiveness, including hardware specifications, network speed, available memory, and queue configurations. Low-Latency Messaging Both Kafka and RabbitMQ are capable of low-latency messaging but use different approaches.

Latency 147
article thumbnail

Five-nines availability: Always-on infrastructure delivers system availability during the holidays’ peak loads

Dynatrace

For retail organizations, peak traffic can be a mixed blessing. While high-volume traffic often boosts sales, it can also compromise uptimes. Five-nines availability: The ultimate benchmark of system availability. The nirvana state of system uptime at peak loads is known as “five-nines availability.”

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

The Ultimate Guide to Database High Availability

Percona

Defining high availability In general terms, high availability refers to the continuous operation of a system with little to no interruption to end users in the event of hardware or software failures, power outages, or other disruptions. Load balancers can detect when a component is not responding and put traffic redirection in motion.

article thumbnail

MySQL Key Performance Indicators (KPI) With PMM

Percona

Number of slow queries recorded Select types, sorts, locks, and total questions against a database Command counters and handlers used by queries give an overall traffic summary Along with this, PMM also comes with Query Analytics giving much detailed information about queries getting executed.

article thumbnail

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.

article thumbnail

High Availability vs. Fault Tolerance: Is FT’s 00.001% Edge in Uptime Worth the Headache?

Percona

Some of the most important elements include: No single point of failure (SPOF): You must eliminate any SPOF in the database environment, including any potential for an SPOF in physical or virtual hardware. Load balancing: Traffic is distributed across multiple servers to prevent any one component from becoming overloaded.

article thumbnail

Compress objects, not cache lines: an object-based compressed memory hierarchy

The Morning Paper

Looking across a set of eight Java benchmarks, we find that only two of them are array dominated, the rest having between 40% to 75% of the heap footprint allocated to objects, the vast majority of which are small. Consider a B-Tree node from the B-tree Java benchmark: Uncompressed, it’s memory layout looks like (a) below. Evaluation.

Cache 61