Remove Availability Remove Benchmarking Remove Cache Remove Design
article thumbnail

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.

article thumbnail

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.

Metrics 130
Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

20X Faster Backup Preparation With Percona XtraBackup 8.0.33-28!

Percona

After the “data dictionary” (DD) engine and DD cache are initialized on a server, the Storage Engines can ask for a table definition. Initializing a DD engine and the cache adds complexity and other server dependencies. Old design (until Percona XtraBackup 8.0.33-27): New design (from Percona XtraBackup 8.0.33-28)

Cache 85
article thumbnail

Percona Monitoring and Management 2 Scaling and Capacity Planning

Percona

These updates are designed to keep databases running at peak performance and simplify database operations. Please note that the focus of these tests was around standard metrics gathering and display, we’ll use a future blog post to benchmark some of the more intensive query analytics (QAN) performance numbers.

article thumbnail

PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

Schema design: Evaluating the database schema design and making adjustments such as partitioning large tables, eliminating redundant data, and denormalizing tables for frequently accessed information can improve performance. This parameter sets how much dedicated memory will be used by PostgreSQL for the cache.

Tuning 52
article thumbnail

MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

This results in expedited query execution, reduced resource utilization, and more efficient exploitation of the available hardware resources. These issues often arise from suboptimal query design, missing or ineffective indexes, or dealing with large datasets. Regularly optimizing query structures is vital.

Tuning 52
article thumbnail

Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

use the TPC-H benchmark to assess Redshift, Redshift Spectrum, Athena, Presto, Hive, and Vertica to find out what works best and the trade-offs involved. We focused on OLAP-oriented parallel data warehouse products available for AWS and restricted our attention to commercially available systems. The design space.