SeerAI & GeoParquet 1.0.0: Revolutionizing Geospatial Data Management and Advanced Spatiotemporal Analytics

September 19, 2023

SeerAI & GeoParquet 1.0.0: A headline announcing the new era of spatiotemporal analytics and data management.

The final release of GeoParquet 1.0.0 is sending waves of enthusiasm throughout the data analytics sector. In a world pivoting increasingly towards extracting knowledge from data, the quest for refined tools to effortlessly manage and analyze complex geospatial data sets has intensified. By integrating SeerAI’s Geodesic platform, with its sophisticated Spatiotemporal analytics engine and data mesh technology, users can effortlessly harness the entirety of their GeoParquet data through a fluid workflow.  The Geodesic platform’s integrated data mesh transforms the data into a web service directly from cloud storage, negating the need for traditional Extract, Transform, and Load (ETL) processes. This results in native services compatible with RESTful, SpatioTemporal Asset Catalog (STAC), OGC web services, Esri GeoServices, GraphQL, JSON, and more.

SeerAI is revolutionizing the way the world understands and interacts with data. Geodesic is cloud native and designed from the ground up for planetary scale data fusion from any data source or file type with an expertise in challenging spatiotemporal data. Geodesic is a powerful capability that enables planetary scale Artificial Intelligence (AI) and Deep Learning workflows against massive standard and geospatial data leveraging the full power of GeoParquet. 

SeerAI’s Proactive Approach with GeoParquet

SeerAI, a pioneer in data mesh technology, has always been a step ahead in recognizing the potential of innovative data solutions. This foresight is evident in our day-one incorporation of the GeoParquet file format within the data mesh. But what exactly does this mean for users?

  1. Seamless Integration with Cloud-native Tools: With SeerAI’s data mesh, users can now easily add their preferred cloud-native tools, including BigQuery, Snowflake, DataBricks, Redshift, Athena, Presto, and Azure Data Lake. This interoperability ensures data does not need be moved, instead data is used natively through the Data mesh which transforms data into a service in a way data scientist, analyst and decision makers can use it.
  2. Efficiency in Data Handling: One of the significant pain points in geospatial data management is the movement of large data files, especially when transitioning between local and cloud environments. SeerAI’s combination of Data Mesh technology and GeoParquet addresses this challenge head-on. Users no longer need to spend excessive time transferring large geospatial files in and out of their cloud-native tools.
  3. Real-time Analysis with Transform on Query Design: In the age of AI, having the capability to apply machine learning and deep learning models on geospatial data in near real-time is a game-changer. SeerAI achieves this through its unique “transform on query” design, enabling users to process planetary-scale data efficiently.
  4. Empowering Large-scale Computation: Whether it’s preparing training data or running complex computations, SeerAI’s infrastructure ensures that you can do so at a planetary scale.

GeoParquet 1.0.0: A Closer Look

GeoParquet 1.0.0 stands out as a trailblazer, focusing squarely on fostering interoperability for Parquet files that represent geospatial data. Key features of this release include:

  • Support for Alternate Coordinate Reference Systems: This feature is pivotal for users who want to conduct analyses without constantly reprojecting from latitude and longitude.
  • Flexibility with Geometry Columns: While multiple geometry columns are permissible, one must be tagged as the ‘primary’ column.
  • Support for Both Spherical and Planar Encodings: This is communicated using the “edges” metadata value, ensuring clarity for users.
  • Compact File Size: One of the most impressive features of GeoParquet is its size efficiency. Compared to popular formats such as GeoPackage, Shapefiles, GeoJSON, and Flatgeobuf, GeoParquet files are considerably smaller. This not only means reduced storage costs but also faster encoding and decoding.
  • Enhanced Performance: The columnar nature of GeoParquet not only offers size advantages but also speed. With benchmarks indicating performance rates that are up to 4 times faster with GeoParquet, it’s clear that this is the future of large-scale geospatial data management.

In Conclusion

The release of GeoParquet 1.0.0 marks a significant leap forward for the data science and geospatial community. When combined with SeerAI’s forward-thinking data mesh technology, the possibilities for efficient geospatial data management and analysis seem limitless. As the world continues to evolve and data becomes ever more crucial, solutions like these will pave the way for a smarter, more connected future.