By integrating Examind Datacube into your data infrastructure, you extend its ability to process very large volumes of georeferenced data in real time.
Datacube gives you a unified interface for a wide range of files and database types
Using the OGC GeoAPI standard, Examind Datacube enables the interconnection of geographic analysis and processing technologies in both Java and Python.
Combining Examind Server with the Datacube and a notebook, we can create a GeoDatascience workshop that provides real-time visualization of the results of elaborate algorithms.
At the core of your infrastructure, Examind Datacube indexes the available resources on the target Datalakes. This comprehensive extension, capable of managing a wide variety of geospatial formats, allows libraries that do not natively support these formats to handle the data.
Examine Datacube features advanced mechanisms (indexing, optimized data readers, scalability...) to extract and transform data on the fly, while guaranteeing performance. The entire DataLake can thus be exploited without any prior data preparation.
All data is accessible through products for which you choose the granularity and structure.
Work with this data in 2D, 3D, or even 4D using programmatic APIs or standard OGC dissemination services.
CS-W & STAC : for data and metadata management
WMS et WMTS : for data visualization with classic services
WCS : for Coverage data distribution
WFS : for vector data distribution
SOS & SensorThings : for distribution of observation data and retrieval of information from connected objects
WPS : for distributed processing
Take advantage of a wide range of processing options for data extraction and manipulation, which can be combined with third-party libraries through the DataCube APIs. This enables you to prototype and then move to production with the processing solution that perfectly meets your needs.Prototyping can be carried out using Notebooks (Jupyter or Zeppelin).