Description
The underlying purpose of RasterFrames is to allow data scientists and software developers to process and analyze geospatial-temporal raster data with the same flexibility and ease as any other Spark Catalyst data type.
raster-frames alternatives and similar packages
Based on the "Big Data" category.
Alternatively, view raster-frames alternatives based on common mentions on social networks and blogs.
-
Deeplearning4J
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn... -
Reactive-kafka
Alpakka Kafka connector - Alpakka is a Reactive Enterprise Integration library for Java and Scala, based on Reactive Streams and Akka. -
Schemer
Schema registry for CSV, TSV, JSON, AVRO and Parquet schema. Supports schema inference and GraphQL API. -
GridScale
Scala library for accessing various file, batch systems, job schedulers and grid middlewares. -
Spark Utils
Basic framework utilities to quickly start writing production ready Apache Spark applications
CodeRabbit: AI Code Reviews for Developers
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
Do you think we are missing an alternative of raster-frames or a related project?
README
™
We've moved!
RasterFrames is now an incubating project at Eclipse Foundation's LocationTech!
- New GitHub repository: https://github.com/locationtech/rasterframes
- LocationTech Project Page: https://projects.eclipse.org/projects/locationtech.rasterframes
Unchanged community resources:
- Documentation: http://rasterframes.io/
- Gitter Chat: https://gitter.im/s22s/raster-frames
Come join the project that's working to make global-scale geospatial processing possible in data frames!
Copyright and License
RasterFrames is released under the Apache 2.0 License, copyright Astraea, Inc. 2017-2018.
*Note that all licence references and agreements mentioned in the raster-frames README section above
are relevant to that project's source code only.