Harvest and MongoDB Integration

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Consolidate Harvest time tracking data in MongoDB for custom reporting. Latenode’s visual editor simplifies the data pipeline, while affordable execution-based pricing helps to manage costs as your team grows. Combine no-code with JS for advanced analysis.

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Harvest

MongoDB

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Harvest and MongoDB

Create a New Scenario to Connect Harvest and MongoDB

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Harvest, triggered by another scenario, or executed manually (for testing purposes). In most cases, Harvest or MongoDB will be your first step. To do this, click "Choose an app," find Harvest or MongoDB, and select the appropriate trigger to start the scenario.

Add the Harvest Node

Select the Harvest node from the app selection panel on the right.

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Harvest

Configure the Harvest

Click on the Harvest node to configure it. You can modify the Harvest URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Run node once

Add the MongoDB Node

Next, click the plus (+) icon on the Harvest node, select MongoDB from the list of available apps, and choose the action you need from the list of nodes within MongoDB.

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Authenticate MongoDB

Now, click the MongoDB node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your MongoDB settings. Authentication allows you to use MongoDB through Latenode.

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Sign In

Run node once

Configure the Harvest and MongoDB Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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The action ID

Run node once

Set Up the Harvest and MongoDB Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Harvest, MongoDB, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Harvest and MongoDB integration works as expected. Depending on your setup, data should flow between Harvest and MongoDB (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Harvest and MongoDB

Harvest + MongoDB + Slack: When a new time entry is created in Harvest, the details are saved to a MongoDB database. A Slack notification is sent to a designated channel informing managers of the new time entry.

Harvest + MongoDB + Jira: When a new time entry is created in Harvest, the data is saved to MongoDB. If the tracked time exceeds a predefined budget (determined outside of this flow), a new Jira ticket is created.

Harvest and MongoDB integration alternatives

About Harvest

Automate time tracking with Harvest in Latenode. Sync time entries to accounting, payroll, or project management. Create flows that auto-generate invoices or trigger alerts for budget overruns. Latenode provides the flexibility to connect Harvest data to other apps and add custom logic, avoiding manual updates and delays.

About MongoDB

Use MongoDB in Latenode to automate data storage and retrieval. Aggregate data from multiple sources, then store it in MongoDB for analysis or reporting. Latenode lets you trigger workflows based on MongoDB changes, create real-time dashboards, and build custom integrations. Low-code tools and JavaScript nodes unlock flexibility for complex data tasks.

See how Latenode works

FAQ Harvest and MongoDB

How can I connect my Harvest account to MongoDB using Latenode?

To connect your Harvest account to MongoDB on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Harvest and click on "Connect".
  • Authenticate your Harvest and MongoDB accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I archive Harvest data in MongoDB for long-term storage?

Yes, you can! Latenode's flexible workflows allow you to automatically archive Harvest data to MongoDB, freeing up space & creating valuable business intelligence.

What types of tasks can I perform by integrating Harvest with MongoDB?

Integrating Harvest with MongoDB allows you to perform various tasks, including:

  • Back up Harvest timesheet data to MongoDB for secure storage.
  • Analyze Harvest data in MongoDB to identify project trends.
  • Create custom reports combining Harvest data with other data sources.
  • Trigger alerts in MongoDB based on Harvest project budget usage.
  • Synchronize Harvest projects with MongoDB collections automatically.

How does Latenode enhance Harvest data analysisusing MongoDB?

Latenode provides visual tools and JavaScript blocks to transform Harvest data before it reaches MongoDB, offering advanced insights without manual coding.

Are there any limitations to the Harvest and MongoDB integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Historical data migration may require initial setup and processing time.
  • Complex data transformations might need custom JavaScript coding.
  • Rate limits on the Harvest API may affect large data synchronization.

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