How to load data from Cockroachdb to S3 Glue

Learn how to use Airbyte to synchronize your Cockroachdb data into S3 Glue 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 Cockroachdb connector in Airbyte

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

Set up S3 Glue for your extracted Cockroachdb 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 Cockroachdb to S3 Glue 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 AWS Environment

Begin by ensuring that you have an AWS account with the necessary permissions to create AWS Glue jobs, access S3 buckets, and read/write data. Set up an S3 bucket where you intend to store the data from CockroachDB. You will also need an IAM role with permissions for Glue and S3.

Step 2: Extract Data from CockroachDB

Use a tool like CockroachDB's built-in SQL client to extract the data. You can execute a `COPY` command to export data from a CockroachDB table into a CSV file. For example:
```
COPY table_name TO 'path/to/output.csv' WITH CSV HEADER;
```
This command will save the data from `table_name` into a CSV file on your local machine or a specified directory accessible to your environment.

Step 3: Install AWS CLI

Ensure that the AWS Command Line Interface (CLI) is installed and configured on your local machine or the server where you're running the export. Use the `aws configure` command to set up your access credentials, default region, and output format.

Step 4: Upload Data to S3

Use the AWS CLI to upload the CSV file to your designated S3 bucket. Run the following command:
```
aws s3 cp path/to/output.csv s3://your-bucket-name/path/to/
```
Replace `your-bucket-name` and `path/to/` with your actual bucket name and desired path within the bucket.

Step 5: Create a Glue Crawler

In the AWS Glue console, create a new crawler to catalog the CSV file in your S3 bucket. Specify the S3 path where your file resides and set up the crawler to detect the schema and create a table in the Glue Data Catalog. Run the crawler to populate the catalog with metadata about your CSV file.

Step 6: Set Up Glue Job

Create a Glue ETL job to transform and process the data if necessary. Configure the job to read from the Glue Data Catalog table created by the crawler. Define any transformations needed using the Glue Studio or by writing a PySpark script.

Step 7: Run and Monitor the Glue Job

Execute the Glue job to process the data as required. Monitor the job execution through the AWS Glue console to ensure successful completion. Once processed, the data will be readily available in the S3 bucket, possibly transformed and in a format suitable for further use.

By following these steps, you can efficiently move data from CockroachDB to S3 using AWS Glue, leveraging AWS's built-in capabilities without relying on any third-party connectors or integrations.