Connect Elasticsearch and DataRobot to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Elasticsearch
Choose an Action
Automatically do this!
- Request a new Action for DataRobot
Enable Integrations or automations with these events of Elasticsearch and DataRobot
Enable Integrations or automations with these events of Elasticsearch and DataRobot
Actions
Create Document
create a doc
Create Document ( without selecting index)
index name is inside the document
Bulk Add Documents to an index
add many documents in one go
Delete Index
delete an index
Create Index
create an index
Search (Fuzzy search)
fuzzy search
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Frequently Asked Questions
To start, connect both your Elasticsearch and DataRobot accounts to viaSocket. Once connected, you can set up a workflow where an event in Elasticsearch triggers actions in DataRobot (or vice versa).
Absolutely. You can customize how Elasticsearch data is recorded in DataRobot. This includes choosing which data fields go into which fields of DataRobot, setting up custom formats, and filtering out unwanted information.
The data sync between Elasticsearch and DataRobot typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Elasticsearch and DataRobot. 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.
About Elasticsearch
Elasticsearch is a powerful, open-source search and analytics engine built on Apache Lucene. It is designed for horizontal scalability, real-time search, and support for multi-tenant environments.
Learn MoreAbout DataRobot
DataRobot is a leading AI platform that enables organizations to harness the power of machine learning and artificial intelligence to drive business insights and decision-making. It offers automated machine learning capabilities, allowing users to build, deploy, and manage AI models efficiently.
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