How good are modern spatial analytics systems?
Spatial data is pervasive. Large amount of spatial data is produced every day from GPS-
enabled devices such as cell phones, cars, sensors, and various consumer based …
enabled devices such as cell phones, cars, sensors, and various consumer based …
The case for learned spatial indexes
Spatial data is ubiquitous. Massive amounts of data are generated every day from billions of
GPS-enabled devices such as cell phones, cars, sensors, and various consumer-based …
GPS-enabled devices such as cell phones, cars, sensors, and various consumer-based …
Enhancing In-Memory Spatial Indexing with Learned Search
Spatial data is ubiquitous. Massive amounts of data are generated every day from a plethora
of sources such as billions of GPS-enabled devices (eg, cell phones, cars, and sensors) …
of sources such as billions of GPS-enabled devices (eg, cell phones, cars, and sensors) …
Data-parallel query processing on non-uniform data
Graphics processing units (GPUs) promise spectacular performance advantages when used
as database coprocessors. Their massive compute capacity, however, is often hampered by …
as database coprocessors. Their massive compute capacity, however, is often hampered by …
How good are modern spatial libraries?
Many applications today like Uber, Yelp, Tinder, etc. rely on spatial data or locations from its
users. These applications and services either build their own spatial data management …
users. These applications and services either build their own spatial data management …
GridMesa: A NoSQL-based big spatial data management system with an adaptive grid approximation model
Due to the urgent demand for managing massive spatial data, various spatial data
management systems built on distributed NoSQL databases have emerged. However …
management systems built on distributed NoSQL databases have emerged. However …
The case for distance-bounded spatial approximations
Spatial approximations have been traditionally used in spatial databases to accelerate the
processing of complex geometric operations. However, approximations are typically only …
processing of complex geometric operations. However, approximations are typically only …
Make the most out of your SIMD investments: counter control flow divergence in compiled query pipelines
Increasing single instruction multiple data (SIMD) capabilities in modern hardware allows for
compiling efficient data-parallel query pipelines. This means GPU-alike challenges arise …
compiling efficient data-parallel query pipelines. This means GPU-alike challenges arise …
DeepSPACE: Approximate geospatial query processing with deep learning
The amount of available geospatial data grows at an ever faster pace. This leads to a
constantly increasing demand for processing power and storage in order to provide data …
constantly increasing demand for processing power and storage in order to provide data …
Geoblocks: A query-cache accelerated data structure for spatial aggregation over polygons
As individual traffic and public transport in cities are changing, city authorities need to
analyze urban geospatial data to improve transportation and infrastructure. To that end, they …
analyze urban geospatial data to improve transportation and infrastructure. To that end, they …