Tue Jun 14 16:38:33 2022

Benchmark Report

The results below were generating using the IMDBench benchmarking suite: github.com/edgedb/imdbench.

Targets

• EdgeDB (Python)
• PostgreSQL (Pyhton, psycopg2)
• PostgreSQL (Python, asyncpg)
• PostgreSQL (Node.js, postgres)
• PostgreSQL (Node.js, pg)
• PostgreSQL (Go, pgx)

Test environment

Linux 5.4.0-117-generic (Ubuntu 20.04, x86_64) on Intel Xeon Processor (Skylake, IBRS)

Duration (per benchmark)

10 seconds

Concurrency

1 clients

Simulated client-to-database latency

~1ms

Overall Results

The charts below show the geometric average of all benchmark results.

Throughput (more is better)

Latency (less is better)

Individual benchmarks

POST /movie (existing cast)

Create a new movie record, linking existing directors and cast.

Throughput (more is better)

Latency (less is better)

Sample Outputs

GET /movie/:id

Get information about a given movie: title, year, directors, cast, recent reviews, and average review rating.

Throughput (more is better)

Latency (less is better)

Sample Outputs

GET /user/:id

Get information about a given user: name and a sample of the latest movie reviews this user authored.

Throughput (more is better)

Latency (less is better)

Sample Outputs