Overview
Developed in Rust with a focus on Python developers, Pathway streamlines the entire ML/AI project lifecycle from prototyping to production. It supports local development, notebook environments, and scaled container deployments. Pathway integrates seamlessly with live data sources such as SharePoint, Google Drive, S3, Delta Tables, Kafka, and over 300 APIs, ensuring that your data remains current and synchronized. Applications can be deployed securely using Docker or Kubernetes, whether on-premises or in any cloud environment, simplifying configurations by eliminating the need for multiple databases and compute engines.
Pathway offers flexibility through ready-to-use code templates applicable to various industries and data types, which can be customized using its extensive library of functions, connectors, and integrations. This enables safe interactions with LLMs and external asynchronous APIs, thereby enhancing your data processing capabilities. By leveraging Pathway, enterprises can unlock new use cases, streamline workflows, and achieve real-time intelligence with ease.
The container uses the community version of Pathway by default. You can access the paid features by providing the license key.
Highlights
- Pathway offers a blend of batch and streaming processing capabilities, powered by a highly efficient Rust engine. This integration allows for real-time intelligence and lightning-fast data transformations, ensuring your enterprise data is always up-to-date and actionable.
- Designed for simplicity and efficiency, Pathway supports local development, notebook environments, and scalable container deployments via Docker or Kubernetes. It seamlessly connects with over 300 APIs and numerous live data sources like SharePoint, Google Drive, S3, and Kafka, providing a robust, synchronized data ecosystem.
- Pathway provides ready-to-use code templates tailored to diverse industries, which can be easily customized using its comprehensive library of functions and integrations. This flexibility enables secure interactions with LLMs and external APIs, empowering enterprises to develop and deploy advanced data processing solutions that align with their specific requirements.
Details
Unlock automation with AI agent solutions

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No refund.
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Delivery details
Container image
- Amazon EKS
- Amazon ECS
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
Added
- Added synchronization group mechanism to align multiple data sources based on selected columns. It can be accessed with pw.io.register_input_synchronization_group.
- pw.io.register_input_synchronization_group now supports the following types of columns: pw.DateTimeUtc, pw.DateTimeNaive, pw.DateTimeDuration, and int.
Changed
- Enhanced error reporting for runtime errors across most operators, providing a trace that simplifies identifying the root cause.
Fixed
- Bugfix for problem with list_documents() when no documents present in store.
- The append-only property of tables created by pw.io.kafka.read is now set correctly.
Additional details
Usage instructions
Run docker image
Pull the Container Image: Ensure you have pulled the container image from Amazon ECR using the provided container image details: docker pull <AWS MP Container image URL>
Launch the Docker Container: Run the following command to launch the Docker container: docker run -ti <AWS MP Container image URL>
Use the Docker Image in a Dockerfile
You can also use this Docker image in a Dockerfile to build a custom script. Here is an example Dockerfile:
FROM <AWS MP Container image URL>
COPY your_script.py /app/your_script.py
CMD ["python", "/app/your_script.py"]
Build your custom Docker image with the following command: docker build -t my-custom-image
Then, run your custom Docker image: docker run -ti my-custom-image
If you are a Pathway Scale or Pathway Enterprise user, you can provide the license key in one of the following ways:
- Set the PATHWAY_LICENSE_KEY environment variable inside the container.
- Specify the key directly as the license_key parameter in the pw.run method.
The license key can be obtained at https://pathway.com/features/Â
Resources
Vendor resources
Support
Vendor support
Support is primarily offered through Pathway's Discord channel and GitHub issues. Users can engage with the community to seek advice, report issues, and collaborate on solutions. This level of support is open and free under BSL 1.1 (Business Source License).
For all support inquiries, including community-driven discussions and issue reports, Pathway commits to providing an initial response within one business day. This ensures that users receive prompt acknowledgment and initial guidance for their queries.
Paid tier customers also have business support with tickets and 24/7 phone support depending on their plan.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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