What is Machine Data?

Put your machine data to work with CrateDB

Machine data is information generated by things

In this data era, machine data is an extremely valuable asset. Data allows organizations to improve their decision-making, the efficiency and security of their operations, and their customer service. Besides, data keeps opening new revenue streams by fostering innovation, with the data volumes growing exponentially due to the rise of technologies like edge computing, IoT, artificial intelligence, and machine learning.

This is where the challenge comes in: volumes are higher than ever. In this new generation of use cases, firehoses of data are continuously coming in, from many different sources and with different formats. These huge data streams need to be processed in real-time, but most data technologies are not prepared for such a workload.

  • 95% of businesses need to manage unstructured data (source: Forbes)
  • 68% of the data available to businesses goes unleveraged (source: IDC)
  • +150 trillion gigabytes of data will be analyzed by 2025 (source: Forbes)

Why is CrateDB different? In one word: architecture

CrateDB is a database purpose-built for machine data, with a unique architecture designed for machine data use cases. Most databases focus on strong consistency; however, machine data is very stable. For these applications, which need to be queried intensively with real-time responses, optimizing performance is way more important than optimizing consistency.

This is precisely what CrateDB does. It applies an eventual consistency model with optimistic concurrency control, maximizing data availability and indexing efficiency. The result? CrateDB returns queries in milliseconds even while processing writes, with in-memory aggregations, JOINs, and sub-selects.


Want to know more?

 Read our Technical Overview

Our customers trust CrateDB for their machine data use cases. Some examples:

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Sensor Data

These use cases include applications continuously recording metrics like vibration, temperature, pressure, sound volume, power levels, acceleration, or telemetry. 

  • Smart cities
  • Industrial equipment monitoring & troubleshooting
  • Anomaly detection
  • Metering and billing
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Log Data

The log data generated by databases, file systems, applications, or web servers is also machine data.

  • eCommerce
  • Security analytics and fraud detection
  • Performance monitoring and optimization
  • Usability analysis
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Network Data

These are use cases involving call detail records (CDRs), network events, packets, and network data.

  • Billing and revenue assurance
  • Capacity planning
  • Network performance degradation
  • Market intelligence
Icon Internet of Things

Internet of Things (IoT)

More and more IoT solutions keep being developed, usually collecting data like GPS and meter readings, biometrics, and device state. 


  • Smart vehicles
  • Smart homes
  • Fitness and health applications
  • Medical and remote diagnostic equipment