Performance insights for the Alumio iPaaS

Our next-gen integration platform is designed to deliver scalable, scheduled, or real-time data exchange for businesses of all sizes.

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Peak performance for dynamic data exchange!

Organizations across industries value the Alumio iPaaS (integration Platform as a Service) for delivering reliable platform uptime and processing thousands of transactions per second. We also support thousands of cloud-native Alumio environments that can easily scale to meet diverse data demands, enabling high-speed real-time integrations or scheduled high-volume data exchanges.

2.1 million data transfers per day

Alumio performance hosting

100k data transfers per minute

Alumio performance hosting

Build scalable integrations

Synchronize data flexibly

Uptime during peak traffic

Boost performance with Alumio’s Data Engines

Alumio Data Engines are powerhouses that help process Tasks like data synchronization, incoming and outgoing requests, and executing background operations. The number of Data Engine determines how many data Routes you can run in parallel through our advanced queue system. Add Data Engines freely to match your processing requirements!

Improve data exchange

Process Tasks faster, handle larger volumes of data exchange, and ensure integrations run uninterrupted, improving overall performance.

Enhance data management

Handling operations in the background, it ensures that core app functionalities are not bogged down by resource-intensive tasks.

Scale up with your data

Manage increased data loads by handling multiple tasks in parallel, manage memory usage effectively, or choose to add-on Data Engines.

Calculate how Data Engines work with Alumio editions

Benefit from both batch-processing and real-time data integrations!

The Alumio iPaaS provides modern businesses with the flexibility they need to process data integration as per different requirements. Whether you're managing large datasets on a scheduled basis or require instant data updates between systems, Alumio’s versatile integration platform ensures that your data is processed the way it’s needed for optimal performance.

Batch-processing integration
(asynchronous integration)

Integrate large volumes of data in scheduled, periodic interval for data that doesn’t need to be processed immediately, ensuring minimal strain in system resources.

Batch processing can be planned during off-peak hours, optimizing resource usage and system performance.

Best-suited for regular, large-scale data synchronizations, such as end-of-day reports, analytics, and billing cycles.

Real-time integration
(synchronous integration)

Import and export data immediately between integrated systems to ensure real-time data updates, for data that needs to be accurately reflected in an instant.

Real-time processing may require continuous resource usage but ensures up-to-date data in applications.

Best suited for live transactions, inventory updates, invoicing, shipment tracking, production status, or detecting IoT device errors.

Import Data

Asynchronous approach - importing data

In this 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. This allowed us to measure the overhead added by Alumio.The following components were used while conducting the test:
‍
An incoming configuration, a range Subscriber (to create 1000 entities per run), an entity Transformer, a data filter, a move-using-pattern Transformer, and a value setter.

Export Data

Asynchronous approach - exporting data

In this scenario, a storage publisher was utilized to process tasks within Alumio. This time, we eliminated 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 performance by executing bulk processing or upgrading the hosting environment.

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

Import & Export Data

Synchronous approach - importhing &
exporting data simultaneously

In this 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, a range Subscriber (to create 1000 entities per run), an entity Transformer, a data filter, a move-using-patter Transformer, and a value setter.

Reliable platform performance for high-volume data exchange

Seasonal sales, marketing campaigns, and new product launches can lead to peak data loads. The Alumio iPaaS delivers horizontally and vertically scalable performance and cloud-native infrastructure that can easily adapt to accommodate larger transaction volumes. Alumio delivers 99.95%+ uptime, enables data caching and buffering, and provides reactivation procedures.