Data Streaming Pipelines in Python. No Kafka. No Flink. Just Python.
A serverless and production-ready setup that empowers everyone in your data team to build and transform event-driven data pipelines.
Define your transformation function
and we run the infra
Zero Infrastructure
No maintenance headaches, just seamless data streaming performance.
Native Python
End-to-end native Python for your pipelines. Forget the Python wrappers and use any Py library you want.
Build in mins
Our underlying infra scales with your needs with the needed latency and data retention.
Create your first
pipeline in minutes
Step-by-step guide to create your pipeline. Within 5 steps your pipeline is ready. You create a complete new pipeline or select from our templates.
Transform in native Python with your favorite library.
GlassFlow offers a flexible, serverless transformation layer. Deploy with one click and no scalability concerns. Start with our templates.
View templatesThis transformation function enriches the incoming data by calling a location API to get latitude, longitude, and region information based on the real-time event
View template
Features
Each feature is built to make your data streaming journey as easy as possible and allow any Py dev to create streams within mins.
Serverless data transformation. Define your function and deploy with a click. We take care of the infra.
Native Python with AI library support. Built for Python. Use any library you want.
Fully managed and data secured service. There is zero stress about maintenance updates or upgrades.
Real-time API connection. Connect to any real-time API like OpenAI, Google Maps, Weaviate, etc.
Alerting and reprocessing. We inform you of unprocessed events. Reprocess faulty events later.
Easy to start and scale infinitely. No message broker needed. No ramp-up time for infra. GlassFlow's robust technology scales for you.
Works with your preferred data stack
Integrate with your data sources and destinations that you are already using. Our Py SDK and our connectors make is easy for you.
View integrations
Supported by the best
See what users experienced with GlassFlow and try it yourself.
“GlassFlow team managed to turn my scattered thoughts regarding the data streaming into a Python masterpiece.”
Anurag Roy@Doorlabs 
“Creating a data pipeline with GlassFlow is incredibly straightforward”
Swapnil Gupta@Deloitte “I am fed up with overcomplicated event-based pipelines. Finally a team that will make my life easier.”
Philippe Brule@aboutphilippe “Love the way they team tackles the complexity of building and sharing streaming pipelines.”
Rakesh Kaswan@KaswanRakesh 
“As a Python dev starting with data streaming, you should absolutely give Glassflow a try.”
Dinesh Marimuthu@Bilthouse “Something is cooking here! Super excited to test your solution.”
Joash Xu@joashxu
