Planetary-scale answers, unlocked.
A Hands-On Guide for Working with Large-Scale Spatial Data. Learn more.
Mo is the co-founder and CEO of Wherobots, and the co-creator of Apache Sedona.
Apache Iceberg and Parquet now support GEO
Geospatial solutions were thought of as “special”, because what modernized the data ecosystem of today, left geospatial data mostly behind. This changes today. Thanks to the efforts of the Apache Iceberg and Parquet communities, we are excited to share that both Iceberg and Parquet now support geometry and geography (collectively the GEO) data types.
Announcing Our 21.5M Series A :: Unlocking Answers to Planetary-scale Questions.
Each day, satellites, drones, applications, and GPS devices generate petabytes of spatial data that can be used to solve real-world problems. But the majority of such data is often stuck in siloed legacy systems or sits idle and disjointed. That’s why we have dedicated our academic and professional careers to answer planetary-scale questions. We’re on a mission to help companies make sense of their data so they can take on issues like how to manage their fleets of vessels and vehicles, where and how to build infrastructure, and determine the best methods to assess and mitigate risk of catastrophic natural disasters.
Introducing Sedona 1.5: Making Sedona the most comprehensive & scalable spatial data processing and ETL engine for both Raster and Vector data
Introducing Sedona 1.5: Making Sedona the most comprehensive & scalable spatial data processing and ETL engine for both Raster and Vector data We’re excited to introduce Apache Sedona‘s 1.5 series, a leap forward in geospatial processing that brings essential features and enhancements. Since our last blog post on the Sedona 1.4 series, Apache Sedona has […]
Unlocking the Spatial Frontier: The Evolution and Potential of spatial technology in Apple Vision Pro and Augmented Reality Apps
The evolution of Augmented Reality (AR) from the realm of science fiction to tangible, practical applications like Augmented Driving, Pokemon Go, and Meta Quest marked a significant shift in how we interact with technology and perceive our surroundings. The recent introduction of Apple Vision Pro underscores this transition, bringing AR closer to mainstream adoption. While […]
Havasu: A Table Format for Spatial Attributes in a Data Lake Architecture
Introduction In the past decade, many organizations have been using BLOB storage (e.g., AWS S3) as a primary storage platform. These organizations collect tons of data and ingest it as files into S3 for its scalability, cost efficiency, and reliability. However, there has since been a need to interact with such data using SQL, which […]
Wherobots Cloud: The Cloud-Native Spatial Analytics Data Platform
According to Gartner, 97% of data collected at the enterprise sits on the shelves without being put into use. That is a shockingly big number, especially given that the data industry got their hopes up a few years back when the Economist published their article “The most valuable resource is no longer oil, it’s data”. […]
Spatial Data, GeoParquet, and Apache Sedona
Apache Parquet is a modern columnar data file format optimized for analytical workload. It is widely adopted in the big data ecosystem. Spatial scientists may also want to use parquet to store spatial data, especially when analyzing large scale datasets on Spark or cloud data warehouses. Problems arise when storing spatial data to parquet files. […]
Harnessing Overture Maps Data: Apache Sedona’s Journey from Parquet to GeoParquet
The Overture Maps Foundation (OMF) has recently released its first open-source Parquet dataset...
Wherobots raises $5.5 Million in seed round to build the data platform for spatial analytics & AI
We are happy to announce that we raised $5.5 Million in seed round led by Clear Ventures and Wing VC. Wherobots Inc. was founded by Mo Sarwat and Jia Yu (the original creators of Open Source Software Apache Sedona) in June 2022 to enable every organization to drive value from data via space and time. […]
