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# Collaborative editing
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# Collaborative Editing
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Allows multiple users to work on the same document simultaneously. This can be done in real-time, so that collaborators can see the changes as they are made. Collaborative editing can be a great way to improve efficiency, as it allows team members to work together on a document without having to wait for others to finish their changes.
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To support collaborative editing, it's crucial to have a backing system that temporarily stores the editing operations of all active users. There are two primary options:
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-*Distributed Cache*: Handles a higher number of `HTTP` requests per second compared to a database approach. For instance, a server with 2 vCPUs and 8GB RAM can handle up to 125 requests per second using a distributed cache.
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-*Database*: With the same server configuration, it can handle up to 50 requests per second.
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-***Distributed Cache***: Handles more HTTP requests per second than a database approach. For example, a server with 2 vCPUs and 8GB RAM can process up to 125 requests per second using a distributed cache. We highly recommend using a distributed cache as a backing system over a database.
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Using the distributed cache or database all the editing operations are queued in order and conflict resolution is performed using `Operational Transformation` Algorithm.
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-***Database***: With the same server configuration, it can handle up to 50 requests per second.
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> *Recommendation* - If you expect average `http` requests per second of your live application as 50 or below, then the database can provide reliable a backing system for operation queue. If you expect average requests per second of your live application as above 50, then the distributed cache is highly recommended backing system.
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Using the distributed cache or database all the editing operations are queued in order and conflict resolution is performed using `Operational Transformation` algorithm.
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> Tips to calculate the average requests per second of your application:
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Assume the editor in your live application is actively used by 1000 users and each user's edit can trigger 2 to 5 requests per second. The total requests per second of your applications will be around 2000 to 5000. In this case, you can finalize a configuration to support around 5000 average requests per second.
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>**Tips**: To calculate the average requests per second of your application Assume the editor in your live application is actively used by 1000 users and each user’s edit can trigger 2 to 5 requests per second. The total requests per second of your applications will be around 2000 to 5000. In this case, you can finalize a configuration to support around 5000 average requests per second.
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>Note: The above metrics are based solely on the collaborative editing module. Actual throughput may decrease depending on other server-side interactions, such as document importing, pasting formatted content, editing restrictions, and spell checking. Therefore, it is advisable to monitor your app's traffic and choose a configuration that best suits your needs.
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>**Note**: The above metrics are based solely on the collaborative editing module. Actual throughput may decrease depending on other server-side interactions, such as document importing, pasting formatted content, editing restrictions, and spell checking. Therefore, it is advisable to monitor your app’s traffic and choose a configuration that best suits your needs.
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#### See Also
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-[Collaborative editing using Redis cache in ASP.NET Core](../../document-editor/collaborative-editing/using-distributed-cache-asp-net-core)
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-[Collaborative editing using Microsoft SQL server in ASP.NET Core](../../document-editor/collaborative-editing/using-database-in-asp-net-core)
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-[Collaborative editing using Java](../../document-editor/collaborative-editing/using-java)
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-[Collaborative editing using Java](../../document-editor/collaborative-editing/using-java)
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