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Average Ratings 0 Ratings
Description
Flow-Like is a locally-operated, open-source workflow automation engine that emphasizes strong typing and allows users to build and execute automation and AI workflows in environments that are self-hosted or offline. By integrating visual, graph-based workflows with deterministic execution, it simplifies the complexities often associated with system maintenance and validation. In contrast to various other tools that depend on untyped JSON, cloud-exclusive backends, or obscure runtime processes, Flow-Like prioritizes explicit and inspectable data flow and execution. This versatility enables workflows to function seamlessly on local machines, private servers, within containers, or on Kubernetes without altering their intended behavior. Built in Rust, the core runtime is optimized for safety, performance, and portability, ensuring it meets high standards. Flow-Like also accommodates event-driven automation, data processing, document ingestion, and AI pipelines, which include typed agent and retrieval-augmented generation (RAG) workflows, utilizing either local or cloud-based models. Ultimately, it is crafted for developers and organizations seeking dependable automation while maintaining comprehensive control over both their data and underlying infrastructure, thereby fostering an environment of transparency and reliability.
Description
GlassFlow is an innovative, serverless platform for building event-driven data pipelines, specifically tailored for developers working with Python. It allows users to create real-time data workflows without the complexities associated with traditional infrastructure solutions like Kafka or Flink. Developers can simply write Python functions to specify data transformations, while GlassFlow takes care of the infrastructure, providing benefits such as automatic scaling, low latency, and efficient data retention. The platform seamlessly integrates with a variety of data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, utilizing its Python SDK and managed connectors. With a low-code interface, users can rapidly set up and deploy their data pipelines in a matter of minutes. Additionally, GlassFlow includes functionalities such as serverless function execution, real-time API connections, as well as alerting and reprocessing features. This combination of capabilities makes GlassFlow an ideal choice for Python developers looking to streamline the development and management of event-driven data pipelines, ultimately enhancing their productivity and efficiency. As the data landscape continues to evolve, GlassFlow positions itself as a pivotal tool in simplifying data processing workflows.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
Amazon Kinesis
Apache Flink
Apache Kafka
Debezium
Docker
Google Cloud Pub/Sub
JSON
Kubernetes
OpenAI
Python
Integrations
Amazon Kinesis
Apache Flink
Apache Kafka
Debezium
Docker
Google Cloud Pub/Sub
JSON
Kubernetes
OpenAI
Python
Pricing Details
$9.99/month
Free Trial
Free Version
Pricing Details
$350 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
TM9657 GmbH
Website
great-co.de
Vendor Details
Company Name
GlassFlow
Founded
2023
Country
Germany
Website
www.glassflow.dev/
Product Features
Workflow Management
Access Controls/Permissions
Approval Process Control
Business Process Automation
Calendar Management
Compliance Tracking
Configurable Workflow
Customizable Dashboard
Document Management
Forms Management
Graphical Workflow Editor
Mobile Access
No-Code
Task Management
Third Party Integrations
Workflow Configuration