Integrations Braintrust TimescaleDB
Braintrust + TimescaleDB

Connect Braintrust and TimescaleDB to Build Intelligent Automations

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Braintrust

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TimescaleDB

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Enable Integrations or automations with these events of Braintrust and TimescaleDB

Enable Integrations or automations with these events of Braintrust and TimescaleDB

Triggers

New project created

New project created

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Frequently Asked Questions

How do I start an integration between Braintrust and TimescaleDB?

To start, connect both your Braintrust and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Braintrust triggers actions in TimescaleDB (or vice versa).

Can we customize how data from Braintrust is recorded in TimescaleDB?

Absolutely. You can customize how Braintrust data is recorded in TimescaleDB. This includes choosing which data fields go into which fields of TimescaleDB, setting up custom formats, and filtering out unwanted information.

How often does the data sync between Braintrust and TimescaleDB?

The data sync between Braintrust and TimescaleDB typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.

Can I filter or transform data before sending it from Braintrust to TimescaleDB?

Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.

Is it possible to add conditions to the integration between Braintrust and TimescaleDB?

Yes, you can set conditional logic to control the flow of data between Braintrust and TimescaleDB. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.

Braintrust

About Braintrust

Braintrust is a decentralized talent network that connects skilled professionals with companies seeking top-tier expertise. It leverages blockchain technology to ensure fair compensation and transparency in the hiring process.

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TimescaleDB

About TimescaleDB

TimescaleDB is a powerful time-series database designed for fast ingest and complex queries, making it ideal for handling time-series data efficiently. It extends PostgreSQL, providing scalability and performance enhancements specifically for time-series workloads.

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