Distributed Computing

Igalia's Distributed Computing team provides targeted solutions for real-time and batch data analysis. We embrace a server-side development model based on distributed systems running in the Cloud, along with new highly-scalable data and computation models. We can help your company solve its BigData challenges.
Perceptive Constructs logo Perceptive Constructs is collaborating with Igalia, contributing specialized machine learning expertise, often useful in data intensive projects.

More and more companies find themselves faced with:

  • business processes generating vast amounts of unexploited data
  • the need to manage huge volumes of unstructured or semi-structured data
  • storage and analysis tools which do not scale
  • the inability to meet system requirements in real time
  • a future which promises even bigger and harder-to-predict workloads

As data generation continues to increase, the demand for smarter and better distributed systems becomes more and more critical. Companies must adapt their systems and look for new data models which work efficiently in distributed environments and under real-time constraints.

We have a team of engineers devoted to building data-intensive information systems at scale, with expertise in real-time web (Node.js) and distributed systems (Erlang, NoSQL). We also provide consulting services on machine-learning and data-mining solutions, including text classification and relevance prediction using a variety of techniques (supervised, unsupervised, active learning).

We have developed several components for retrieving, processing and analyzing Social Media streams, using Node.js at server-side, NoSQL technologies for distributed storage (Redis and Cassandra) and
machine-learning algorithms.

If your company is experiencing BigData problems and is ready to explore innovative solutions using Open Source frameworks and tools to maximize the value of your company's data, Igalia should be your partner.

  • Distributed Systems
  • NoSQL
  • Real-Time Data Analysis
  • Machine-Learning
  • BigData
  • Cloud