Editor's recommendation:
I have promoted GeoSpark before, but now it has been incubated by Apache, and it is called Sedona. Students who are interested in spatial big data, please don’t let it go, practice hard... In addition, I have written about Sedona, welcome to contribute and share with the official account.
The following article comes from Little Rabbit GIS, author Little Rabbit GIS
Little Rabbit GIS. 
https://mp.weixin.qq.com/s/cqU2jhoYPIMJ_U6jJ6CWiA#
With GIS as the core, exchange IT knowledge
1、Apache Sedona
Sedona is a distributed geographic information computing engine based on Spark. It was originally GeoSpark, and was later included and incubated by Apache. It was renamed Sedona. Compared with traditional analysis tools such as ArcGIS and QGIS, Sedona can provide better distributed spatial analysis.
Apache Sedona™ (incubating) is a cluster computing system for processing large-scale spatial data. Sedona extends Apache Spark/SparkSQL with a set of out-of-the-box Spatial Resilient Distributed Datasets (SRDDs)/SpatialSQL to efficiently load, process and analyze large-scale spatial data across machines.
2、GeoSpark
GeoSpark is an open source in-memory cluster computing system for processing large-scale spatial data. It is a combination of traditional GIS and Spark. GeoSpark extends RDDs to form spatial RDDs (SRDDs), efficiently partitions SRDD data elements across machines, and introduces novel parallelized spatial (geometric operations, following the Open Geosptial Consortium (OGC) standard) transformations and operations (for SRDDs ), providing a more intuitive interface for users to write spatial data analysis programs. GeoSpark extends the SRDD layer to perform spatial queries (e.g., range queries, KNN queries, and join queries) on large-scale spatial datasets. After retrieving geometric objects in the Spatial RDD layer, users can call the spatial query processing operations provided in GeoSpark's spatial query processing layer.
3、GeoMesa
GeoMesa is a distributed basic engine open sourced by locationtech for processing geographic data. It is a suite of geographic big data processing tools. It enables large-scale geospatial query and analysis on distributed computing systems. Use GeoMesa open source to help users manage and use massive spatio-temporal data from the Internet of Things, social media, and mobile applications. GeoMesa supports storing massive spatio-temporal data in Accumulo, HBase, Google Bigtable and Cassandra databases, and provides efficient indexes to read and query these data. And supports quick query by specifying spatial conditions (distance and range). In addition, GeoMesa also provides near real-time stream processing of spatio-temporal data based on Apache Kafka.
【Store, index, query, and transform spatio-temporal data at scale
in HBase, Accumulo, Cassandra, Redis, Kafka and Spark.】
4、GeoTrellis
GeoTrellis is a scala library and framework for processing raster data based on Apache spark. It can efficiently read/write and manipulate rasters. It implements map operations and vector-to-raster conversion tools. It can render raster data into PNG images. Metadata converted to JSON.
GeoTrellis solves three core problems
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1) Create scalable, high-performance geographic information processing WEB services
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2) Create distributed geographic information processing services to process massive datasets
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3) Complete parallel geographic information processing operations to take advantage of the multi-core architecture
GeoTrellis can import data (Tiff) from local, HDFS, S3 to local, HDFS, Accumulo, HBASE, CASSANDRA, S3, etc. There are many options, and it is processed in parallel by Spark cluster, which is equivalent to GeoTrellis has realized distributed tile cutting.
5、GeoWave
GeoWave is a software library that connects distributed computing frameworks and the scalability of key/value stores with modern geospatial software to store, retrieve, and analyze massive geospatial datasets.
GeoWave is an open source library for storing, indexing and searching multidimensional data in sorted key/value stores. It includes implementations that support OGC spatial types (up to 3 dimensions) and bounded and unbounded temporal values. GeoWave's geospatial support builds on the GeoTools project extensibility model. This means that it can natively integrate with any GeoTools-compatible project, such as GeoServer and UDig, and can bring in GeoTools-compatible data sources.
6、GeoDocker
GeoDocker is a collection of Docker images encapsulating distributed geoprocessing platforms based on GeoTrellis, GeoMesa and GeoWave. The focus is on providing integration between these projects and exposing geoprocessing functionality in the Hadoop ecosystem.
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Integrating GeoTrellis, GeoWave and GeoMesa into a Unified Platform
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Provide a real and convenient distributed integration testing environment
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Support for deploying GeoDocker to Amazon EMR
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Explore and support other deployment options such as DC/OS and ECS
7、Shepherds
Alibaba Dharma Institute, the core engine of Alibaba Cloud's self-developed space-time infrastructure (PaaS layer), which integrates infrastructure capabilities such as heterogeneous computing parallel acceleration on the cloud, OSS large-scale storage, and the upper layer and RDS PostgresSQL database, POLARDB for PG /Oracle cloud native database, HBase big data and other integration provide free but professional spatio-temporal data storage, query and analysis computing capabilities for cloud computing basic products.
By being compatible with the PostGIS interface, Ganos has almost plug-and-play, fast ecological compatibility, and all PostGIS-compatible codes do not need to be changed.
BACKPACK
More technical solutions are in the collection
The editor previously wrote an article discussing the open source GIS architecture scheme . The processing of traditional general spatial data is aimed at breaking away from the scope of commercial GIS. Today, with the vigorous development of big data and cloud computing, it is also a constant task to sort out the related technologies of spatial big data. The ongoing process for learning exchanges.
Spatial big data technology fish diagram