Performance Reports

The Alumio iPaaS (integration Platform as a Service) boosts performance in several business areas. While streaming real-time integrations, it supports business process orchestration and guarantees a high speed of delivery.

When it comes to hassle-free integrations and effortless data synchronization, Alumio is second to none! As evidenced in our new performance report, Alumio can handle data transfers at peak-hours easily!

2.1 million data
transfers per day

Alumio SMB performance hosting

100,000 data
transfers per minute

Alumio custom multi-threaded hosting

Discover our new performance insights

The following performance insights gathered by Alumio experts include results from asynchronous and synchronous processing scenarios. This involved testing three scenarios importing data, exporting data, and synchronously importing and exporting data.

The performance report has been compiled after rigorous testing with the default 'Professional edition' hosting setup - Alumio version 3.13.0, 8GB, 2 cores. The testing was carried out in the region eu-west-2a (London).

Asynchronous approach - importing data (creating tasks)

Throughput data metrics

For the first scenario, a data seeder was utilized to create tasks within Alumio. We eliminated the influence of external factors by utilizing a data seeder instead of an API call, database query, GraphQL query, etc. With this approach, we were able to measure the overhead added by Alumio.

The following components were used while conducting the test: an incoming configuration, range Subscriber (to create 1000 entities per run), an entity transformer, a data filter, move using a pattern (data transformer), and a value setter.

Asynchronous approach - exporting data (processing tasks)

Throughput data metrics

For this scenario, a storage publisher was utilized to process tasks within Alumio. This time, we eliminate the influence of external factors by utilizing a storage publisher instead of an API call, database query, GraphQL query, etc. Since each task gets processed sequentially, there was no need for optimizations. However, it is possible to further improve the performance by executing bulk processing or upgrading the hosting environment.

The following components were used - an outgoing configuration, storage publisher (to process 1000 tasks sequentially per run), an entity transformer, a data filter, move using a pattern (data transformer), and a value setter.

Synchronous approach - importing & exporting data simultaneously

A synchronous integration approach creates and processes tasks at the same time. As data gets imported (tasks are created), it is immediately exported (tasks are processed). Similar to the asynchronous strategy, we used a data seeder to import the data and a storage publisher to export the data. This eliminates the influence of external factors and we measured the overhead added by Alumio.

The following components were used - an incoming configuration, a range subscriber (to create 1000 entities per run), an outgoing configuration, a storage publisher (to process 1000 tasks sequentially per run), an entity transformer, a data filter, move using a pattern (data transformer), and a value setter.

An overview of the new performance results

Asynchronous Approach

Average time taken for 1000 tasks: 42s 776ms

Median time taken for 1000 tasks: 44s 490ms

Average tasks per second: 23.378

Median tasks per second: 22.478

Synchronous Approach

Average time taken for 1000 tasks: 4s 466ms

Median time taken for 1000 tasks: 4s 374 ms

Average tasks per second: 223.914

Median tasks per second: 228.623

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Marketing actions such as TV commercials, social campaigns, or promotions can cause peak loads. Alumio understands the importance of performance and therefore provides robust and scalable solutions that scale with peak loads.

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