COMPARATIVE ANALYSIS OF CLOUD SERVICES FOR GEOINFORMATION DATA PROCESSING

O.Y. Nedosnovanyi, O.I. Cherniak, V.V. Golinko
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Abstract

The article is devoted to a comparative analysis of cloud services for processing geographic data. It describes in detail the services - Google Cloud, Amazon Web Services and Microsoft Azure - that provide tools for storing, processing and analyzing large amounts of geographic data. The article also describes the parameters of geoinformation services, the access algorithm, and examples of program code for processing satellite data. The article describes such opportunities and limitations of using cloud services as automation, security and scalability. The conclusions and recommendations for further development of geographic information systems based on cloud services are provided. Services. Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) offer a variety of geodata storage solutions. These solutions include object storage, such as Amazon S3, Azure Blob Storage, and Google Cloud Storage, as well as geospatial databases, such as Amazon RDS, Azure Cosmos DB, and Google Cloud Firestore. In addition, each of these services provides a set of services for analyzing and processing geographic information data. For example, AWS offers services such as Amazon Athena, Amazon Redshift, and AWS Glue, which allow you to run SQL queries, conduct analytics, and integrate geodata with other services. Azure offers services such as Azure SQL Database, Azure Databricks, and HDInsight, which provide capabilities for processing and analyzing geographic data. GCP also provides services such as BigQuery, Dataflow, and Dataproc, which allow you to perform analytical operations and process large amounts of geodata. Support for integration with various geo-tools is important for analysis, such as AWS, Amazon Location Service, Amazon Ground Truth, and Amazon Rekognition, which allow you to work with geodata at different levels of complexity. Azure has Azure Maps, which provides services for geocoding, routing, and visualization of geodata. GCP also offers Google Maps Platform, which provides extensive integration with geographic technologies such as routing, geocoding, and map visualization. All these processes will allow for more efficient data processing. Keywords: cloud technologies,
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地理信息数据处理云服务的对比分析
本文致力于对处理地理数据的云服务进行比较分析。它详细描述了谷歌云、亚马逊网络服务和微软Azure等服务,这些服务提供了存储、处理和分析大量地理数据的工具。本文还介绍了地理信息服务的参数、访问算法以及处理卫星数据的程序代码示例。本文从自动化、安全性和可伸缩性等方面描述了使用云服务的机会和限制。最后,对基于云服务的地理信息系统的进一步发展提出了建议。服务。亚马逊网络服务(AWS)、微软Azure和谷歌云平台(GCP)提供各种地理数据存储解决方案。这些解决方案包括对象存储,如Amazon S3、Azure Blob storage和Google Cloud storage,以及地理空间数据库,如Amazon RDS、Azure Cosmos DB和Google Cloud Firestore。此外,这些服务中的每一个都提供一组用于分析和处理地理信息数据的服务。例如,AWS提供Amazon Athena、Amazon Redshift和AWS Glue等服务,这些服务允许您运行SQL查询、进行分析并将地理数据与其他服务集成。Azure提供了Azure SQL Database、Azure Databricks和HDInsight等服务,这些服务提供了处理和分析地理数据的能力。GCP还提供BigQuery、Dataflow和Dataproc等服务,允许您执行分析操作并处理大量地理数据。支持与各种地理工具的集成对于分析非常重要,例如AWS、Amazon Location Service、Amazon Ground Truth和Amazon Rekognition,它们允许您处理不同复杂级别的地理数据。Azure有Azure Maps,它提供地理编码、路由和地理数据可视化服务。GCP还提供谷歌地图平台,该平台广泛集成了地理技术,如路由、地理编码和地图可视化。所有这些过程将允许更有效的数据处理。关键词:云技术;
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