Data Pipelinesstreamparse
Run Python code against real-time data streams using Apache Storm.
- Status
- UnmaintainedNo commits in 746 days.
- Last checked
- Aging · Sep 4, 2026
- License
- Open source
- Pricing
- Free tier · from $0
What it is
Streamparse is a tool that allows developers to process and analyze real-time streaming data with Python, leveraging the power of Apache Storm for scalability and fault tolerance.
Streamparse stands out by providing a Pythonic interface to Apache Storm's powerful real-time data processing capabilities, making it easier for developers familiar with Python to work with complex streaming data.
When it fits — and when it doesn’t
A good fit for
Teams needing to process and analyze large volumes of real-time streaming data with Python.
Developers looking to integrate Apache Storm's capabilities into their Python applications.
Look elsewhere if
Projects that require a managed service for stream processing, as streamparse requires self-hosting.
Applications where the use of Python is not feasible or preferred.
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited integrations with other data processing tools
Streamparse primarily integrates with Apache Storm, limiting its compatibility with newer or alternative stream processing frameworks
- 02
Small and less active community
GitHub activity shows fewer contributors and lower issue resolution rates compared to more popular data processing tools
What it does well
Real-time data processing with Python
Integration with Apache Storm for scalability and fault tolerance
Distributed stream processing capabilities
Pricing
- Free tier
- YesOpen source — free to use
- Paid from
- $0
- Model
- Flat rate
- Enterprise plan
- No
Pricing not independently confirmed — check the vendor’s page.
Performance benchmarks
How Fast Is It?
Set up streamparse
Setup steps, common gotchas and what to check after 30 days.