Amazon Athena Serverless Interactive Query Service

When it comes to building your data strategy and architecture, it's essential to understand which data warehouses should be candidates for consideration. Typically, teams will be asking themselves answers like "How do I install and configure a data warehouse?" or "Which data warehouse solution will help me to get the fastest query times?" or "Which of my analytics tools are supported?" This article covers key features and benefits of five widely used data lake and warehouse solutions supported by Openbridge to help you choose the right one: How to Choose a Data Warehouse Solution that Fits Your Needs. If you have answers, feel free to reach out to us.

Typically, you will not need services for Athena. Most customers are up and running using their Athena data quickly. However, if you need support, we do offer expert services. There may be situations where you have specific needs relating to Athena data. These situations can require expert services to tailor Athena data to fit your requirements. Ultimately, our mission is helping you get value from data, and this can often happen more quickly with the assistance of our passionate expert services team.

Yes, typically, Athena requires authorization to access your data. You would provide us with the Athena authorizations, so we can properly connect to their system. However, there are some situations where companies like Athena can "push" data to us. In those cases, we provide them with connection details to our API or our Data Transfer Service. Once they have those details, they use that information to connect, authenticate, and deliver data to us.

Yes! Amazon suggests compression and file splitting can have a significant impact to speed up Athena queries significantly. The smaller data sizes mean optimized queries, and it will also reduce network traffic with data stored in Amazon S3 to Athena. When your data is splittable, Openbridge will do this Athena optimization for you. This allows the execution engine in Athena to optimize the reading of a file to increase parallelism and reduce the amount of data scanned. In the case of an unsplittable file, then only a single reader can read the file. This only happens in the case of smaller files (generally less than 128 MB).

Yes! Amazon suggests the use of columnar data formats. We have chosen to use Apache Parquet vs other columnar formats. Parquet will store data efficiently with column-wise compression, including different encoding and compression, based on data type. Openbridge will automatically handle the conversion of data to Parquet format, saving you time and money, primarily when Athena executes queries that are ad hoc in nature. Also, using Parquet-formatted files means reading fewer bytes from Amazon S3, leading to better Athena query performance.

Athena use Presto, a commercialized version of a Facebook project. Presto is an open-source SQL query engine that powers the AWS Athena service. Unlike Presto, you only pay for the queries you run, no servers to manage. Check out the article What is Presto, Facebook Presto Database, PrestoSQL, or PrestoDB? A powerful SQL query engine

Is there a looker athena connection? How about for Tableau or Power BI?

Amazon does charge for the service. For the current costs, check out the AWS pricing page

Check out the AWS documentation.