Understand transactions in Ninox

Learn how Ninox executes read and write transactions.

Ninox runs database actions as transactions. A transaction groups one or more operations into a single execution step. In practice, this means Ninox handles reading data and changing data in different ways.

Read transactions

A read transaction looks up data without changing it.

Typical examples are:

• filtering records in a table
• running a query to find matching records
• reading values to display them in the app

When Ninox starts a read transaction, it works with the data state that was current at that moment. Changes saved by other users during that same query are not part of that result.

Ninox can process many read transactions at the same time. One user reading data does not usually block another user from reading data.

Write transactions

A write transaction changes data.

Typical examples are:

• creating a record
• editing a field value
• deleting a record
• clicking a button that updates data
• running logic that writes values back to the database

Only one write transaction runs at a time. Other write transactions wait until the current one finishes. This is usually not a problem because most write transactions finish very quickly.

Automations such as On create and On update run inside the same write transaction that caused them.

Use your knowledge of transactions to design a high-performance app

Good Ninox logic does more than return the right result. It should also run predictably, avoid blocking other users, and stay easy to maintain.

If Ninox seems slow or briefly unresponsive, a longer write transaction may be blocking the queue.

This happens when one action takes much longer than usual, and later write actions must wait. Common causes are:

• calls to external services, for example with http(...)
• large data evaluations combined with select
• complex logic inside buttons or automations that updates many records

Avoid these causes by keeping the write logic focused and short.

Follow these rules of thumb:

• read and prepare data first when possible
• keep API calls out of critical write flows when possible
• avoid repeated select queries inside loops
• test buttons and automations with realistic data volumes
• split large updates into smaller steps when possible

A practical way to think about it:

• Use read transactions to inspect data.
• Use write transactions only when you need to save a change.
• The less work a write transaction has to do, the smoother the app feels for everyone.