Machine-Generated Data Analytics

Perform analytics directly on machine-generated data without needing to reformat and load into a database.


Gain insight from your machine processes without ETL

Examples of machine-generated data analytics where RAW is applicable include:

  • Product Traceability within a manufacturing environment, where each machine creates files resulting from processing events in proprietary formats
  • Predictive Maintenance scenarios where machine sensor readings, maintenance schedules and performance events can be fed by RAW directly into machine learning models
  • DevOps / DataOps failure investigation where analysis of distributed components’ log files requires combined query and correlation of events

Create data products directly from these types of datasets, and expose as APIs quickly and efficiently.

RAW Features and Benefits

SQL on Databases, Files & APIs

Query and reuse any data source directly without ETL

APIs as a Service

Spend all your effort on business logic and not infrastructure


10x less code - scale your team to deliver more, faster

DataOps and Data-as-Code

Deliver and iterate faster with higher quality

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Interrogating machine generated data for diagnostics

Cesar Matos shows us how RAW can give fast answers to a complex data problem where engineers need to investigate issues plaguing operational systems.


Introducing the RAW Data Product Platform

Data Products as a Service: A low-code, collaborative platform as a service, where you pay as you go for data APIs.


RAW Labs to Participate in "SmartDataLake: Sustainable Data Lakes for Extreme-Scale Analytics" EU Initiative

RAW Labs SA has been awarded a contract to participate in the highly visible SmartDataLake project funded by the EU. RAW Labs will provide its NoDB Platform for the project....

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