Remove c
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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

Redis Server: 5.07, x86/64. MongoDB server: 4.4.2, BangDB server: 2.0.0, Workload C: Read only. Application example: user profile cache, where profiles are constructed elsewhere (e.g., The latency table is following for test C and since it was read only test hence there is no update latency figure here.

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How to Assess MySQL Performance

HammerDB

GHz 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids) Up to 20% higher compute performance than z1d instances Up to 50 Gbps of networking speed Up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (EBS) We can also verify these capabilities by running some simple benchmarks on the different subsystems.

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A MyRocks Use Case

Percona

The use case is the TPC-C benchmark but executed not on a high-end server but on a lower-spec virtual machine that is I/O limited like for example, with AWS EBS volumes. The TPC-C dataset I used was with a scale of 200. TPC-C on MyRocks. MyRocks handles indexes in a similar fashion.

Storage 55
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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

Connection pooling: Minimizing connection overhead and improving response times for frequently accessed data by implementing mechanisms for connection pooling and caching strategies. PostgreSQL performance optimization is an ongoing process involving monitoring, benchmarking, and adjustments to maintain high-performing PostgreSQL databases.

Tuning 52
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Tuning PostgreSQL Database Parameters to Optimize Performance

Percona

Bear in mind that while optimizing PostgreSQL server configuration improves performance, a database developer must also be diligent when writing queries for the application. This parameter sets how much dedicated memory will be used by PostgreSQL for cache. It is just a guideline, not the exact allocated memory or cache size.

Tuning 55
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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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HammerDB for Managers

HammerDB

HammerDB is a software application for database benchmarking. Databases are highly sophisticated software, and to design and run a fair benchmark workload is a complex undertaking. The Transaction Processing Performance Council (TPC) was founded to bring standards to database benchmarking, and the history of the TPC can be found here.