Fiber
Python library for distributed computing on modern clusters.
- Status
- Not yet determined
- Last checked
- Unverified
- License
- Open source
- Pricing
- Free tier · from $0
What it is
Fiber is a Python-based distributed computing library designed to facilitate efficient computation across modern computer clusters, making it easier to handle large-scale data processing tasks.
Fiber stands out as a Python library specifically optimized for efficient distributed computing on modern clusters, offering scalability and performance benefits over general-purpose libraries.
When it fits — and when it doesn’t
A good fit for
Teams needing to scale Python-based data processing tasks across multiple machines
Research groups working with large datasets and requiring high computational power
Look elsewhere if
Projects that require real-time data streaming capabilities
Small-scale projects where distributed computing is not necessary
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited third-party library integrations
Lacks native support for popular ML frameworks like TensorFlow and PyTorch, requiring custom integration efforts
- 02
Performance bottlenecks on small clusters
Optimized for large-scale distributed environments; may show suboptimal performance in smaller cluster setups due to overhead
What it does well
Efficient distributed computing across clusters
Scalable for large-scale data processing tasks
Optimized for modern hardware and network environments
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 Fiber
Setup steps, common gotchas and what to check after 30 days.