Amazon Web Services (AWS) is a famous cloud platform that can be operated to run applications and store data. It provides many tools for developers, including the Simple Storage Service (S3), Lambda, and DynamoDB.

What is the SSIS equivalent in AWS?

AWS Glue

AWS Glue is a data preparation tool that can extract, transform, and load data. It has many similarities with SSIS in that it can perform ETL operations on data stored in Amazon S3 or other cloud storage services. The most important difference between AWS Glue and SSIS is that AWS Glue does not support any SQL Server databases (for now).

AWS Step Functions

Step Functions by AWS is a service that allows you to organize the components of distributed applications and microservices through visual workflows. It is a serverless method to develop and operate applications. Step Functions uses an event-driven system that responds to various events, including changes in data or state (e.g., uploading a file), new messages via an HTTP endpoint, scheduled intervals for performing tasks (e.g., sending emails), and more.

Data Pipeline

Data Pipeline is a service for automating data integration, data movement, and data transformation in AWS. It is used for ETL (extract, transform, load) applications. It allows you to define your data’s source, destination, and transformation through a simple web interface or command line tool.

Data Pipeline is a managed service that provides:

  • A graphical user interface where you can define the source(s), destination(s), and transformations of your data;
  • Automated execution of those tasks on an hourly basis;
  • Support for relational databases like Oracle or MySQL as well as non-relational ones like MongoDB;

Kinesis Data Streams

The Kinesis Data Streams service is a managed service that makes it easy to collect, process, and analyze real-time data streams. With Kinesis Data Streams, you can:

  • Collect and store data streams of any size in a fault-tolerant repository available in real-time at the rate you specify.
  • Process the collected data with Lambda functions or stream it to applications such as Amazon Elastic MapReduce (EMR), Amazon QuickSight, Amazon Machine Learning, and other services that support Kinesis Data Streams integration via application programming interfaces (APIs).

SSIS is useful and has its place, but there are other options.

Data integration can be achieved through various tools, and SSIS is one of them. However, AWS offers several other options that can be used in conjunction with or as a substitute for SSIS in certain scenarios. Although SSIS has advantages and is useful in some cases, it may only sometimes be necessary when working with cloud databases like Amazon Redshift. If your ETL needs are straightforward, or if you only need to move files within your hard drive, there might be simpler ways to accomplish these tasks than using SSIS.

AWS Data Pipeline

AWS Data Pipeline is a service that allows you to automate data movement between various AWS services. It is an ETL tool that allows you to move data between Amazon S3, Amazon DynamoDB, and Amazon Redshift. In other words, it’s like SSIS in that it lets you move data from one place to another, unlike SSIS because of limitations (e.g., no schema change).

AWS Lambda

AWS Lambda is a serverless computing platform. You can run code without provisioning or managing servers, paying only for the compute time you consume–there are no servers to manage, patches to apply, and so on.

You write your code in a programming language (JavaScript, Python, C#), then AWS Lambda executes it on demand as part of an event-driven architecture. The result? A highly scalable system that automatically adapts as needed while also making it easy to build applications that respond quickly to new data or user requests

Amazon DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. It’s especially useful for applications that process large data or do so at high volumes but can also be used for smaller projects.

DynamoDB uses the key-value store model, which means there are no tables or schemas–you create and access items using their keys. You can use DynamoDB to store data in tables (similar to how you would use an RDBMS), documents (similar to MongoDB), graphs (similar to Neo4J), sets (similarly to Redis), or streams (which allows you to stream events from one place across multiple sources).

There is no one-to-one equivalent of SSIS in AWS.

The answer to your question is complex. Although SSIS is a potent tool, AWS has several ways to solve the same problem. Each tool has its strengths and weaknesses, but they all have one thing in common: they were built by Amazon engineers who understand their customers’ daily problems. Let’s examine some of the most famous options for performing ETL with Kinesis Data Streams, Data Pipelines, and Lambda functions (which can also be utilized for batch processing).


The takeaway from this article is that there is no one-to-one equivalent of SSIS in AWS. It’s important to understand the differences between these tools and how they can be used together. For example, you can use Step Functions to orchestrate an AWS Data Pipeline job that uses DynamoDB as a source or sink. On the other hand, if your organization already invests in SSIS, there may only be a little need for switching over to another toolset unless there are specific reasons why it would make sense (such as needing something more flexible than SQL Server Integration Services).

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