

Athena uses the Presto SQL query engine for low latency data analysis, enabling users to run queries against large datasets in Amazon S3 using ANSI SQL. With standard SQL to run queries, users can analyze their data directly within Amazon S3.
Amazon athena vs redshift software#
The software also scales automatically, meaning that users can run interactive queries in parallel for faster processing and analyses of larger datasets.

In addition to data log processing, Athena users can perform ad-hoc analyses of their data. For example, Amazon Kinesis Data Firehose can load streaming data into Amazon Redshift to quickly produce near real-time analytics. The Amazon Redshift Data API enables database connections and data access from programming languages and platforms supported by the AWS SDK, including Java, Ruby, Go, Python, PHP, Node.js and C++. Users can load and transform data into the Redshift data warehouse with Data Integration Partners to access data from third-party sources.Īdditionally, the system can access data from cloud-native, traditional, containerized, serverless web services-based and event-driven applications. It can parse data from Apache logs, TSV, JSON and CSV formats. Redshift’s streaming capabilities allow users to connect and ingest data from multiple Kinesis data streams at once with SQL. Redshift utilizes structured and semi-structured data from Amazon S3, data warehouses, operational databases, data lakes and third-party data sets to develop actionable insights. Athena supports complex data types and SerDe libraries for accessing various data formats, including Parquet, CSV, Avro, JSON and ORC. With the Athena Query Federation SDK, users can build connectors to integrate with any data source. The Athena Data Source Connectors that run on AWS Lambda can allow users to access data from Amazon DynamoDB, Apache HBase, Amazon DocumentDB, Amazon Redshift, AWS CloudWatch, AWS CloudWatch Metrics and JDBC-compliant relational databases. Glue displays new and modified table and partition definitions from the discovered data within the platform console. It can automatically crawl data services to access data and populate the data catalog, where the fully-managed ETL capabilities can then process the data and prepare it for analysis. Amazon S3 stores important data across multiple facilities, and users can also integrate with AWS Glue to create a unified metadata repository. The Athena software can access and analyze data that is stored in Amazon S3, relational, non-relational, object and custom data sources. Amazon Redshift software comparison Data access Must-read big data coverageĭata Scientist Survey: Do Tech Leaders Believe the AI Hype?ĩ best data science tools and software of 2023 The product can access and analyze both structured and semi-structured data using SQL. What is Amazon Redshift?Īmazon Redshift is a data warehousing tool that enables users to access and analyze their data with machine learning. Buyers of the product can use standard SQL to prepare and analyze their datasets or integrate with other business intelligence tools for increased functionality. SEE: Cloud data warehouse guide and checklist (TechRepublic Premium) What is Amazon Athena?Īmazon Athena is a cloud-based query service for large-scale data analysis. We will be comparing each of these solutions so that you can determine which product would best suit your data processing needs. Fortunately, Amazon offers cloud-based products for data management and query processing.īut while Amazon Athena and Amazon Redshift are both data warehouse tools that enable users to access and analyze their data, the products differ in their features, capabilities and functionality. For more info, visit our Terms of Use page.Ī data service can be a valuable asset for organizations that utilize big data and datasets from multiple sources.

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Amazon Athena vs Amazon Redshift: Compare data warehousing platformsĪmazon Athena and Amazon Redshift are data warehouse software solutions.
