How to load data from Polygon Stock API to Redshift

Learn how to use Airbyte to synchronize your Polygon Stock API data into Redshift within minutes.

Building your pipeline or Using Airbyte

Airbyte is the only open source solution empowering data teams  to meet all their growing custom business demands in the new AI era.

Building in-house pipelines
Bespoke pipelines are:
  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.
After Airbyte
Airbyte connections are:
  • Reliable and accurate
  • Extensible and scalable for all your needs
  • Deployed and governed your way
All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and AI Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Polygon Stock API connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Redshift for your extracted Polygon Stock API data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Polygon Stock API to Redshift in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Setup Complexities simplified!

You don’t need to put hours into figuring out how to use Airbyte to achieve your Data Engineering goals.

Simple & Easy to use Interface

Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.

Guided Tour: Assisting you in building connections

Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.

Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes

Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Raman Singh

Tech Lead at Symend

Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

Learn more
Chase Zieman headshot

Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more

Rupak Patel

Operational Intelligence Manager

"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."

Learn more

How to Sync to Manually

Step 1: Set Up Your Amazon Redshift Cluster

Begin by setting up an Amazon Redshift cluster. Log in to the AWS Management Console, navigate to the Redshift service, and create a new cluster. Choose the appropriate node type and number of nodes based on your data size and query performance needs. Ensure that the cluster is launched in a VPC with appropriate security group settings to allow incoming connections from your client machine.

Configure your Redshift cluster's security group to allow inbound traffic on the port Redshift uses (default is 5439). Set up an IAM role with the necessary permissions to access Redshift and add it to your cluster. Make sure to also configure network settings to allow your client machine to access the Redshift cluster, either through public IP or VPC peering.

Sign up for an account on Polygon.io and obtain your API key. The API key is necessary to authenticate requests to the Polygon Stock API. Keep this key secure as it provides access to your API data.

Create a Python script (or use another programming language of your choice) to extract data from the Polygon Stock API. Use the `requests` library in Python to send HTTP GET requests to the API endpoints. For example, to get stock prices, you might use:
```python
import requests

api_key = 'YOUR_API_KEY'
url = f'https://api.polygon.io/v1/last/stocks/{ticker}?apiKey={api_key}'
response = requests.get(url)
data = response.json()
```
Parse the JSON response to extract the necessary data fields for your Redshift tables.

Transform the extracted data into a format that is compatible with Redshift. This often means converting JSON data into a CSV format. Use libraries like `pandas` in Python to clean and transform the data:
```python
import pandas as pd

df = pd.json_normalize(data)
df.to_csv('data.csv', index=False)
```
Ensure that the CSV file matches the schema of your Redshift table.

Upload the transformed CSV file to an Amazon S3 bucket. Use the AWS CLI or Boto3 library in Python to perform the upload:
```bash
aws s3 cp data.csv s3://your-bucket-name/data.csv
```
Make sure the IAM role associated with your Redshift cluster has permissions to access this S3 bucket.

Use the `COPY` command in Redshift to load data from the S3 bucket into your Redshift table. Connect to your Redshift cluster using a SQL client, and execute:
```sql
COPY your_table_name
FROM 's3://your-bucket-name/data.csv'
IAM_ROLE 'arn:aws:iam::your-account-id:role/your-redshift-role'
DELIMITER ','
IGNOREHEADER 1
CSV;
```
Adjust the options in the `COPY` command to match your data format and Redshift table schema. This step efficiently loads your data into Redshift for further analysis.

By following these steps, you can successfully move data from the Polygon Stock API into Amazon Redshift without relying on third-party connectors or integrations.