Rivery enables organizations on AWS to build and deploy ELT pipelines and workflows in minutes, so they can deliver insights from data while reducing data delivery friction.
In this blog, we share some important information about these AWS targets, as well as provide access to best practices for loading the data, so you can:
- Instantly create powerful data pipelines with ready-made, pre-built data workflow kits
- Load data in a matter of clicks
- Build no-code data pipelines at scale
Amazon Redshift is a fast, fully managed data warehouse for analyzing data using standard SQL and Business Intelligence (BI) tools.
It enables organizations to run complex analytic queries against petabytes of structured data (ETL to Redshift or ETL from Redshift), using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
To make sure the data you’re loading to your Redshift cluster works seamlessly, and that your table structures or views won’t be harmed during the process, it is important to review these best practices, considerations, and requirements for using Redshift and Rivery. To get started, click here.
Amazon Simple Storage Service (Amazon S3) enables object storage with a simple web service interface to store and retrieve any amount of data from anywhere on the web.
S3 can be used as the primary storage for cloud-native applications, as a bulk repository or data lake for analytics, as a target for backup and disaster recovery, and with serverless computing.
For best practices, considerations, and requirements for Rivery with S3, click here.
Amazon Athena is an interactive query service that makes it easy to analyze data directly in Amazon S3 using standard SQL.
Athena is serverless, so there is no infrastructure to manage, and users pay only for the queries that they run.
With a few actions in the AWS Management Console, users can point Athena at the data stored in Amazon S3 and begin using standard SQL to run ad-hoc queries and get results in seconds.
To learn about how you can create an AWS user for Rivery, a workgroup in Amazon Athena, what is the connection procedure, and what is the configuration process, click here.
Amazon Aurora is a fully managed relational database engine that’s compatible with MySQL and PostgreSQL. MySQL and PostgreSQL combine the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. The code, tools, and applications that are used with existing MySQL and PostgreSQL databases can also be used with Aurora.
To learn about how easy it is to set up Aurora as a target in Rivery, as well as how to create requirements for loading and configuration, click here.
Connect with Rivery
Rivery offers an end-to-end, easy-to-use, and cost-effective ELT solution for data ingestion and workflow orchestration on AWS with:
- More than 200+ fully-managed data connectors
- No-code interface
- Enhanced security and privacy
- Multi-tenant workspaces
To see it in action in your environment, we invite you to access all of the solution’s features for 14 days for free. To get started click here.