Disco
A lightweight, open-source framework for distributed computing based on MapReduce, designed for handling massive data with minimal code.
Score
30
User Rating
3.0
Free/Trial Support
Supported
Starting Price
--
Last Updated
Apr 23, 2026
Overview
What is Disco?
Disco is an open-source distributed computing framework that uses the MapReduce paradigm to process large datasets efficiently. It was developed at Nokia Research Center in 2008 and supports data distribution, job scheduling, and real-time querying of billions of data points.
What is Disco used for?
Top Features
- Easy installation on multiple OS
- Efficient data-locality-preserving IO
- Supports profiling and debugging
- Random access to data and results
- Run jobs in any language via worker protocol
- Build and query indices with billions of keys
How to use Disco?
Install Disco on Linux, Mac OS X, or FreeBSD, write Python scripts for map and reduce functions, and run jobs on a cluster to parallelize computations. It includes tools for indexing and querying data, with support for profiling and debugging.
Alternative Tools
No alternative tools found
Pros & Cons
Pros
- Open-source and free
- Powerful for large-scale data processing
- Easy to use with Python
- Supports real-time querying
- Active development and community support
Cons
- Alpha version may have bugs
- Limited to MapReduce paradigm
- Requires cluster setup for full benefits
Use Cases
- Log analysis
- Probabilistic modelling
- Data mining
- Full-text indexing
- Word frequency computation
Disco Pricing
Free Plan
No detailed pricing information available
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