Data Processing

Centrally managed data processing pipelines accelerated by auto-scaling cloud compute infrastructure deliver faster processing speeds and stability - without the complexity.

Stream Processing

  • Analyze data events asynchronously – as data arrive, in batch, or on a schedule – so that servers only do work when called on.
  • Configure downstream actions like emails, SMS messages, application alerts, machine learning model predictions, or REST API calls.
  • Visualize time-series data stream for real-time analysis and monitoring of high-frequency data loads of any scale.
Stream Processing

Batch Processing

  • Dynamically provision the optimal quantity compute resources based on the volume and specific resource requirements of the batch jobs submitted.
  • Focus on analyzing results and solving problems. There is no need to install and manage batch computing software or server clusters.
  • Identify duplicate data points and determine how they should be handled.
  • Schedule batch jobs to run on a periodic basis.
Batch Processing

Iterative Processing

  • Rapidly train and re-train AI / machine learning models by iterating over data in-memory rather than on disk.
  • Run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk.
Iterative Processing

Featured Case Studies

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Turnkey Projects in 6 to 12 Weeks

C3 provides trials of the C3 Applications, C3 AI Suite, and C3 Enterprise Data Lake. Trials range in cost based on duration and include C3 professional services and cloud infrastructure services.

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