Rockset

Rockset is a serverless search and analytics engine that allows you to create live dashboards and real-time data APIs on DynamoDB, Kafka, S3 and more.

Integrate the Rockset API with the Go API

Setup the Rockset API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Rockset and Go remarkably fast. Free for developers.

Add Documents with the Rockset API

Add documents to a collection in Rockset. Learn more at https://docs.rockset.com/rest/#adddocuments.

 
Try it
Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
Try it
Create API Key with the Rockset API

Create a new API key for the authenticated user.

 
Try it
Create Integration with the Rockset API

Create a new integration with Rockset. Learn more at https://docs.rockset.com/rest/#createintegration

 
Try it

Overview of Rockset

Rockset API is a modern API for real-time query on complex data. With Rockset,
you can build applications with routinely updated datasets, such as web traffic
logs, machine generated data, sensor data, ad-tracking data, and IoT device
data, to unlock real-time insights and actionability. In this article, we’ll
discuss the various types of applications you can build with Rockset API.

Rockset gives you the power to:

  • Quickly ingest and index data from a variety of sources such as Kafka,
    MongoDB and Amazon S3.
  • Perform complex analytical queries regardless of data complexity, structure
    and size.
  • Perform interactive computing on large volumes of data using SQL.
  • Build web or mobile applications with sophisticated analytics capabilities.

Here are some example applications you can build using Rockset API:

  • Personalized Shopping Experiences: Leverage data from many customer
    touchpoints, such as social media, web and app usage, customer support
    tickets and customer reviews, to build personalized shopping experiences.
  • Automated Fraud Detection: Create and monitor automated fraud detection
    systems that ingest and analyze various types of data in real-time to detect
    anomalous user behaviors.
  • Smart IoT: Create a connected infrastructure that lets you develop and deploy
    intelligent applications that can understand, store and analyze IoT data
    streams.
  • Machine Learning: Build applications that can quickly access, prepare and
    analyze data used for predictive analysis.
  • Log Management and Analytics: Collect, monitor and analyze log data from
    various sources to monitor system performance and alert on anomalies.

Connect Rockset

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    rockset: {
      type: "app",
      app: "rockset",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.rs2.usw2.rockset.com/v1/orgs/self/users/self`,
      headers: {
        "Authorization": `ApiKey ${this.rockset.$auth.apikey}`,
      },
    })
  },
})

Connect Go

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
package main

import (
	"fmt"

	pd "github.com/PipedreamHQ/pipedream-go"
)

func main() {
	// Access previous step data using pd.Steps
	fmt.Println(pd.Steps)

	// Export data using pd.Export
	data := make(map[string]interface{})
	data["name"] = "Luke"
	pd.Export("data", data)
}