Raw-Data Analytics¶
CrateDB provides real-time analytics on raw data stored for the long term
In all domains of real-time analytics where you absolutely must have access to all the records, and can’t live with any down-sampled variants, because records are unique, and need to be accounted for within your analytics queries.
If you find yourself in such a situation, you need a storage system which manages all the high-volume data in its hot zone, to be available right on your fingertips, for live querying. Batch jobs to roll up raw data into analytical results are not an option, because users’ queries are too individual, so you need to run them on real data in real time.
With CrateDB, compatible to PostgreSQL, you can do all of that using plain SQL. Other than integrating well with commodity systems using standard database access interfaces like ODBC or JDBC, it provides a proprietary HTTP interface on top.
- Tags:
Analytics Long Term Storage
- Related:
Time Series Data • Time Series Long Term Storage • Machine Learning
- Product:
Bitmovin Insights¶
Multi tenant data analytics on top of billions of records.
CrateDB enables use cases we couldn’t satisfy with other database systems, also with databases which are even stronger focused on the time series domain.
CrateDB is not your normal database!
– Daniel Hölbling-Inzko, Director of Engineering Analytics, Bitmovin
- Industry:
Broadcasting Media Transcoding Streaming Media
- Tags:
Event Tracking Real-Time Analytics Multi Tenancy SaaS
- Related:
CrateDB provides the backbone of Bitmovin’s real-time video analytics platform
How Bitmovin uses CrateDB to monitor the biggest live video events
Bitmovin: Real-Time Analytics
Bitmovin, as a leader in video codec algorithms and as a web-based video stream broadcasting provider, produces billions of rows of data and stores them in CrateDB, allowing their customers to do analytics on it.
One of their product’s subsystems, a video analytics component, required to serve real-time analytics on very large and fast-moving data, so they needed to find a performing database at the right cost.
The use-case of Bitmovin illustrates why traditional databases weren’t capable to deal with so many data records and keep them all available for querying in real time.