A complete comparison of Starburst and EMR

Some additional exploration

Amazon EMR, Amazon Elastic MapReduce, or AWS EMR, which is it?

Formerly known as Amazon Elastic MapReduce, the official name of the service is Amazon EMR.

What are the benefits of EMR?

Amazon EMR offers a wide range of benefits for its customers, including elasticity, simple pricing, integration with other AWS services like AWS Data Pipeline, Amazon Cloudwatch, Amazon Redshift, EC2, Amazon VPC, Amazon Kinesis, and more. Use of APIs to programmatically manage your clusters. Also the ability to facilitate data transformation (ETL).

What are the challenges with EMR?

While Amazon EMR is a powerful tool, it does come with its own set of challenges:

• Complexity: Amazon EMR can be complex to set up and manage, especially for users who are not familiar with the Hadoop ecosystem. This complexity can lead to increased time and resources spent on setup and management.
• Automation: While Amazon EMR does provide some level of automation, it is not sufficient for all use cases. For example, data teams, more often than not, need to write custom scripts or use third-party tools to automate certain tasks that are automated out of the box in platforms like Starburst Galaxy.
• On-Demand vs. Reserved Instances: Choosing the right instance type can be challenging, and the burden rests with the data team. On-demand instances offer flexibility but can be more expensive, while reserved instances require a longer-term commitment but can be more cost-effective.
• Resource Intensive: Amazon EMR is resource-intensive, which can lead to increased costs across headcount and unnecessary spending on resource availability if not managed properly. Without built-in capabilities, users need to carefully monitor and manage their resource usage to avoid unnecessary costs.
• Security: While Amazon EMR does provide robust security features, setting up and managing these features can be complex. Users need to carefully consider their security requirements and ensure they are correctly implemented.
• Single cloud: The service only runs on AWS, so for multi-cloud environments, you now have to run multiple big data analytics platforms.
• Basic support: Customers of EMR Trino only have access to standard AWS support and must rely on the open-source community to support their mission-critical applications.

What is the difference between EMR and Amazon Athena?

Also see how Starburst, which offers better performance, scale, optionality, governance, access, collaboration, sharing, and more, compares to Athena.

Amazon EMR and Amazon Athena are both AWS services that handle big data, but they do so in different ways.

• Amazon EMR is a managed Apache Hadoop framework that supports other frameworks, including OS Trino and Presto, that process large amounts of data across Amazon EC2 instances. However, it can be more expensive compared to Athena and Starburst, especially when you are not processing any data.
• Amazon Athena is an interactive query service (also built on top of OS Trino) that is best for ad-hock queries, which makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage.

While both services are designed to process big data, EMR provides a platform for open-source frameworks like Trino, Presto, Hadoop, and Apache Spark (each framework has its own version of EMR) and is ideal for complex, long-running jobs. In contrast, Athena is designed for quick, ad-hoc queries directly against data stored in S3. Starburst Galaxy, powered by Trino, is great for both.

What is the cost of EMR?

Amazon EMR pricing is considered simple. You pay a per-second rate for every second you use, with a one-minute minimum. Though the pricing for EMR may seem cost-effective, once you configure the full architecture to add in every other AWS service to set up a fully functional platform, the costs quickly begin to rise. This differs from platforms like Starburst, where the price is inclusive of all the capabilities from compute, access, governance, security, and more.

What is the difference between EMR and Amazon EC2?

Amazon EC2 (Elastic Compute Cloud) provides the raw compute capacity in the cloud (i.e., virtual machines); EMR is a service built on top of EC2 to process large amounts of data using big data frameworks. Both services only run on AWS.

What is the difference between EMR and Amazon Redshift?

Amazon EMR is a cloud service for big data processing using Amazon EC2 instances. On the other hand, Amazon Redshift is a cloud data warehouse service from AWS. Both services only run on AWS.

How are file systems used in Amazon EMR Trino?

In Amazon EMR, the EMR File System (EMRFS) is an implementation of HDFS that all Amazon EMR clusters use for reading and writing regular files from Amazon EMR directly to Amazon S3. EMRFS provides the convenience of storing persistent data in Amazon S3 for use with Hadoop while also providing features like data encryption.

When it comes to Trino (formerly known as PrestoSQL) in Amazon EMR, it uses its own S3 filesystem for the URI prefixes s3://, s3n://, and s3a://. This allows Trino to read and write tables that are stored in Amazon S3 or S3-compatible systems. This is accomplished by having a table or database location that uses an S3 prefix rather than an HDFS prefix.