Quickstart

This guide walks you through creating a dataset, adding a table, inserting data, and running your first query.

Prerequisites

• A Catalyzed account (sign up here)
• An API token (see API Tokens)

Quick Start

1. Set up your API token

   Export your token as an environment variable:

   export API_TOKEN="cat_tok_..."

2. Get your team ID

   Get your teams

   cURL

   curl https://api.catalyzed.ai/teams \
     -H "Authorization: Bearer $API_TOKEN"

   TypeScript

   const response = await fetch("https://api.catalyzed.ai/teams", {
     headers: { Authorization: `Bearer ${process.env.API_TOKEN}` },
   });
   const { teams } = await response.json();
   const teamId = teams[0].teamId;

   Python

   import os
   import requests
   
   response = requests.get(
       "https://api.catalyzed.ai/teams",
       headers={"Authorization": f"Bearer {os.environ['API_TOKEN']}"}
   )
   teams = response.json()["teams"]
   team_id = teams[0]["teamId"]

   Note the teamId from the response.

3. Create a dataset

   Create dataset

   cURL

   curl -X POST https://api.catalyzed.ai/datasets \
     -H "Authorization: Bearer $API_TOKEN" \
     -H "Content-Type: application/json" \
     -d '{
       "teamId": "YOUR_TEAM_ID",
       "name": "My First Dataset"
     }'

   TypeScript

   const response = await fetch("https://api.catalyzed.ai/datasets", {
     method: "POST",
     headers: {
       Authorization: `Bearer ${process.env.API_TOKEN}`,
       "Content-Type": "application/json",
     },
     body: JSON.stringify({
       teamId: teamId,
       name: "My First Dataset",
     }),
   });
   const dataset = await response.json();

   Python

   response = requests.post(
       "https://api.catalyzed.ai/datasets",
       headers={"Authorization": f"Bearer {os.environ['API_TOKEN']}"},
       json={"teamId": team_id, "name": "My First Dataset"}
   )
   dataset = response.json()

   Note the datasetId from the response.

4. Create a table

   Create table

   cURL

   curl -X POST https://api.catalyzed.ai/dataset-tables \
     -H "Authorization: Bearer $API_TOKEN" \
     -H "Content-Type: application/json" \
     -d '{
       "datasetId": "YOUR_DATASET_ID",
       "tableName": "users",
       "fields": [
         {"name": "id", "arrowType": "utf8", "nullable": false},
         {"name": "name", "arrowType": "utf8", "nullable": false},
         {"name": "email", "arrowType": "utf8", "nullable": false},
         {"name": "created_at", "arrowType": "timestamp", "nullable": false}
       ],
       "primaryKeyColumns": ["id"]
     }'

   TypeScript

   const response = await fetch("https://api.catalyzed.ai/dataset-tables", {
     method: "POST",
     headers: {
       Authorization: `Bearer ${process.env.API_TOKEN}`,
       "Content-Type": "application/json",
     },
     body: JSON.stringify({
       datasetId: dataset.datasetId,
       tableName: "users",
       fields: [
         { name: "id", arrowType: "utf8", nullable: false },
         { name: "name", arrowType: "utf8", nullable: false },
         { name: "email", arrowType: "utf8", nullable: false },
         { name: "created_at", arrowType: "timestamp", nullable: false },
       ],
       primaryKeyColumns: ["id"],
     }),
   });
   const table = await response.json();

   Python

   response = requests.post(
       "https://api.catalyzed.ai/dataset-tables",
       headers={"Authorization": f"Bearer {os.environ['API_TOKEN']}"},
       json={
           "datasetId": dataset["datasetId"],
           "tableName": "users",
           "fields": [
               {"name": "id", "arrowType": "utf8", "nullable": False},
               {"name": "name", "arrowType": "utf8", "nullable": False},
               {"name": "email", "arrowType": "utf8", "nullable": False},
               {"name": "created_at", "arrowType": "timestamp", "nullable": False}
           ],
           "primaryKeyColumns": ["id"]
       }
   )
   table = response.json()

   Note the tableId from the response.

5. Insert data

   Insert rows

   cURL

   curl -X POST "https://api.catalyzed.ai/dataset-tables/YOUR_TABLE_ID/rows?mode=append" \
     -H "Authorization: Bearer $API_TOKEN" \
     -H "Content-Type: application/json" \
     -d '[
       {"id": "1", "name": "Alice", "email": "[email protected]", "created_at": "2024-01-15T10:00:00Z"},
       {"id": "2", "name": "Bob", "email": "[email protected]", "created_at": "2024-01-15T11:00:00Z"},
       {"id": "3", "name": "Charlie", "email": "[email protected]", "created_at": "2024-01-15T12:00:00Z"}
     ]'

   TypeScript

   await fetch(`https://api.catalyzed.ai/dataset-tables/${table.tableId}/rows?mode=append`, {
     method: "POST",
     headers: {
       Authorization: `Bearer ${process.env.API_TOKEN}`,
       "Content-Type": "application/json",
     },
     body: JSON.stringify([
       { id: "1", name: "Alice", email: "[email protected]", created_at: "2024-01-15T10:00:00Z" },
       { id: "2", name: "Bob", email: "[email protected]", created_at: "2024-01-15T11:00:00Z" },
       { id: "3", name: "Charlie", email: "[email protected]", created_at: "2024-01-15T12:00:00Z" },
     ]),
   });

   Python

   requests.post(
       f"https://api.catalyzed.ai/dataset-tables/{table['tableId']}/rows?mode=append",
       headers={"Authorization": f"Bearer {os.environ['API_TOKEN']}"},
       json=[
           {"id": "1", "name": "Alice", "email": "[email protected]", "created_at": "2024-01-15T10:00:00Z"},
           {"id": "2", "name": "Bob", "email": "[email protected]", "created_at": "2024-01-15T11:00:00Z"},
           {"id": "3", "name": "Charlie", "email": "[email protected]", "created_at": "2024-01-15T12:00:00Z"}
       ]
   )

6. Query your data

   Query the table

   cURL

   curl -X POST https://api.catalyzed.ai/queries \
     -H "Authorization: Bearer $API_TOKEN" \
     -H "Content-Type: application/json" \
     -d '{
       "sql": "SELECT * FROM users ORDER BY created_at DESC",
       "tables": {"users": "YOUR_TABLE_ID"}
     }'

   TypeScript

   const response = await fetch("https://api.catalyzed.ai/queries", {
     method: "POST",
     headers: {
       Authorization: `Bearer ${process.env.API_TOKEN}`,
       "Content-Type": "application/json",
     },
     body: JSON.stringify({
       sql: "SELECT * FROM users ORDER BY created_at DESC",
       tables: { users: table.tableId },
     }),
   });
   const results = await response.json();
   console.log(results.rows);

   Python

   response = requests.post(
       "https://api.catalyzed.ai/queries",
       headers={"Authorization": f"Bearer {os.environ['API_TOKEN']}"},
       json={
           "sql": "SELECT * FROM users ORDER BY created_at DESC",
           "tables": {"users": table["tableId"]}
       }
   )
   results = response.json()
   print(results["rows"])

What’s Next?

You’ve created a dataset, table, and run your first query! Here’s what to explore next:

• Tables - Learn about schemas, indexes, and advanced querying
• Files - Upload CSV, JSON, or PDF files for processing
• Pipelines - Automate workflows with AI-powered pipelines
• API Reference - Explore all available endpoints