Top AWS Data Ingestion Tools for Seamless Data Pipelines

Data ingestion is a crucial step in performing any data-driven task, such as data analytics and business intelligence initiatives. It lays the necessary groundwork required for smoother execution of subsequent processes like transformation and storage.

By using Amazon Web Services (AWS) tools for data ingestion, you can benefit from scalable infrastructure, reduced operational complexity, and faster time-to-insight. In this article, you will discover the top thirteen AWS data ingestion tools to help you build high-performance pipelines and facilitate quick data movement.

What Does AWS Data Ingestion Tool Mean?

AWS data ingestion tool is a service or solution that allows your organization to collect or import data efficiently into the AWS ecosystem. With this tool, you can streamline data transfer from databases, IoT devices, log files, or external systems into the AWS Cloud for storage or analysis.

How AWS Data Ingestion Tools Work?

AWS data ingestion tools allow you to extract your data from sources like relational databases, IoT devices, or web applications to collect relevant information. You can either capture and process data in real-time using Amazon Kinesis or in large batches using AWS Snowball. Some tools even let you automate data movement and transformation.

The ingested data is then loaded into AWS storage solutions like Amazon S3 or Redshift. This dataflow ensures that raw data is efficiently shifted and organized for deeper analysis while maintaining scalability and speed.

3 Data Ingestion Tools Offered By AWS

AWS offers several tools to help your organization ingest data effectively without compromising on throughput and reliability. Below is a list of the top three AWS data ingestion tools that you should consider:

1. Amazon Kinesis

Amazon Kinesis is a suite of AWS services you can leverage to perform real-time collection and analysis of high-volume data and video streams. It offers low-latency data ingestion, enabling your organization to gain immediate insights and respond promptly to emerging trends.

You can use standard SQL or Apache Flink for real-time processing and even invoke Lambda functions to transform incoming data. Amazon Kinesis also lets you optimize query performance by facilitating effective grouping and partitioning of records into multiple shards.

2. AWS Glue

AWS Glue, a serverless data integration service, simplifies the data discovery, preparation, and movement for machine learning and application development. It is an AWS ETL tool that automatically creates Python and Scala scripts to help you build ingestion pipelines.

The platform features a Data Catalog that acts as a central repository for metadata, enhancing governance and accessibility. AWS Glue also supports schema versioning and evolution, ensuring your data’s consistency over time.

3. AWS DataSync

AWS DataSync is a data transfer service that enables you to automate data movement between on-premises storage and Amazon S3, Amazon EFS, and Amazon FSx. This tool uses an on-premise software agent to connect with your existing file system through a Network File System (NFS) protocol. With this feature, your team does not have to write scripts or modify applications that work with AWS APIs.

With DataSync, you can migrate data at speeds up to ten times faster than most open-source tools. It offers you the flexibility to conduct data migration with other notable cloud storage services. Using AWS DataSync is easy and cost-effective because you only need to pay for the data you copy.

10 AWS Data Ingestion Tools We Recommend

Data ingestion tools simplify the process of extracting and unifying varied data from multiple locations. These encompass IoT devices, downstream applications, file protocols, and on-premise storage centers. Here are the top ten AWS data ingestion tools that you can leverage for your organization’s smooth data transfer operations.

1. Airbyte

Airbyte is a reliable data movement platform that empowers you to extract structured, semi-structured, and unstructured data from dispersed sources. With its intuitive UI and no-code pre-built 550+ connectors, you can copy this data into databases, data warehouses, or data lakes, including AWS services like Datalake, Redshift, S3, Kinesis, DynamoDB, and more.

Apart from these pre-built connectors, you can build custom ones using Connector Builder. This solution features an AI assistant that prefills the configuration fields and provides intelligent suggestions for fine-tuning the development process. For advanced customization, Airbyte offers flexible options to build pipelines through its API, Terraform Provider, and PyAirbyte.

2. AWS Snowball Edge

AWS Snowball is a service that helps you quickly migrate large volumes of data between Amazon S3 and on-premises data storage locations. Snowball Edge is a type of pre-configured Snowball device that can conduct local processing and edge-computing workloads within isolated operating environments. This tool is most useful when you want to move data from remote or disconnected locations, such as an oil and gas rig, mining sites, and moving vehicles like ships.

3. AWS Database Migration Service (DMS)

AWS Database Migration Service (DMS) is one of the most popular AWS Migration Tools available. Using it, you can migrate data from a database to an AWS service. The database can be either on-premises, in an Amazon RDS DB instance, or in your EC2 instance.

With AWS DMS, you get the flexibility to conduct data integration for several homogeneous and heterogeneous database migrations, such as Oracle, PostgreSQL, MongoDB, and more. This AWS ingestion tool helps you maintain high data availability and minimal downtime even while transferring terabyte-size datasets. You only have to pay for the compute resources and additional log storage that you use during data movement.

4. AWS Transfer Family

AWS Transfer Family lets you securely store data in Amazon Simple Storage Service or Amazon Elastic File System. Through this AWS data ingestion tool, you can simplify data transfer from specified workflows into AWS. It facilitates secure and reliable transfer through Secure File Transfer Protocol (SFTP), File Transfer Protocol Secure (FTPS), File Transfer Protocol (FTP), and Applicability Statement 2 (AS2). When using the AWS Transfer family web app, you must keep in mind that there are limitations for maximum search results and breadth per query.

5. Amazon OpenSearch Ingestion

A subset of Amazon OpenSearch Service, OpenSearch Ingestion is a fully managed serverless data collector. It enables you to deliver real-time log, metric, and trace data to OpenSearch Service and Serverless collections without relying on Logstash and Jaeger. With this AWS data collection tool, you can provision ingestion pipelines directly within the AWS Management Console. You do not have to look after the management and scaling of software and servers. OpenSearch Ingestion automatically provisions and delivers the data to your specified domain.

6. AWS Data Pipeline

AWS Data Pipeline is a web service that allows you to define data-driven workflows along with the parameters for transforming your data. In this tool, each new task is dependent on the successful completion of the previous tasks. You must create Amazon EC2 instances to schedule pipelines and run tasks on the AWS Data Pipeline. However, this service is currently under maintenance, making it unavailable for new customers.

7. AWS IoT Core

AWS IoT provides you with cloud services that enable you to connect your IoT devices to AWS cloud services or any other devices. The IoT Core message broker supports devices and clients that use MQTT, HTTP protocols, and MQTT over WSS protocols to publish messages. Using the AWS IoT Core for LoRaWAN, you can manage wireless low-power, long-range Wide Area Network (LoRaWAN) devices with ease.

8. Fivetran

Fivetran is one of the widely used AWS ETL tools that offers pre-configured connectors to move data into AWS services, like Amazon Redshift, S3, and others. You can also deploy Fivetran through the AWS Marketplace. Additionally, Fivetran supports AWS PrivateLink, which enables security between data sources and AWS destinations.

9. AWS Direct Connect

AWS Direct Connect allows you to establish a direct connection from an on-premises network to more than one VPC. The tool utilizes industry-standard 802.1Q VLANs to help you integrate with Amazon VPCs through private IP addresses. You can configure VLANs through three different types of virtual interfaces (VIFs). AWS Direct Connect provides you with two types of connections: Dedicated and Hosted. However, this AWS tool is not encrypted by default.

10. AWS Storage Gateway

AWS Storage Gateway is a hybrid cloud storage tool that lets you integrate your existing on-premises infrastructure with AWS cloud storage. If you are already working with Windows workloads, you can leverage Storage Gateway to store and access data. This can be done by using native Windows protocols, SMB and NFS. AWS Storage Gateway offers four tools: Amazon S3 File Gateway, FSx File Gateway, Tape Gateway, and Volume Gateway. The former two are most often used with Microsoft workloads.

AWS Data Ingestion Tools: Use Cases

AWS data ingestion tools can empower your organization to support multiple use cases and bring out the true potential of its data assets. Here are some ways you can leverage these tools:

• Migrating Databases to AWS Cloud: You can utilize AWS DMS to migrate your on-premises databases to AWS-managed services with minimal downtime.‍
• Ingesting IoT Data for Monitoring: AWS IoT Core allows you to collect, ingest, and manage data from IoT devices for applications like smart home monitoring or industrial systems.
• ‍Data Transfer for AI/ML Training: You can use AWS DataSync and Snowball to ingest massive datasets into AWS for training machine learning models on Amazon SageMaker.

How to Pick The Right AWS Data Ingestion Tool?

Choosing the right AWS data ingestion tool depends heavily on your organization’s specific requirements. Here's a breakdown of certain factors that you can consider:

• Data Sources: You should identify the types of sources (streaming data, IoT devices, SaaS applications) you work with, as different tools are optimized for different source types.‍
• Transformation Needs: Based on the quality of your incoming data, you need to decide whether to transform it during the ingestion process. This helps you further categorize the tools depending on the availability of built-in transformation capabilities.‍
• Data Destination: Knowing which AWS platform (S3, Redshift, or DynamoDB) you will utilize for downstream data processing can guide your choice of ingestion tool. The tool you select must integrate with your target destination effortlessly.‍
• Ease of Use: You should consider the tool’s complexity, its learning curve, and your team’s expertise. Opting for a platform that is easy to use and manage can be ideal for your organization.‍
• Cost: By evaluating each tool’s data transfer, processing, and storage costs, you can achieve your performance requirements while adhering to budget constraints.

Closing Thoughts

AWS data ingestion tools are reliable and budget-friendly options if your organization is deeply invested or dependent on Amazon. The AWS ecosystem provides you with a multitude of options to collect, process, and manage different types of data. Once you consolidate your data, you can ensure its quality, security, and validity for all operations in your organization. You can even leverage AWS ML and data processing capabilities, data centers across regions, generative AI, and foundation models to develop robust customer solutions.