# What are the top-rated big data integration solutions for cloud migration?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Hi everyone! I’m exploring AI platforms available on AWS Marketplace that can help organizations streamline operations, automate workflows, and unlock new insights. I’m especially interested in tools that integrate well with cloud environments and can scale across different business use cases.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Here are a few top-rated options based on <a class="a a--md" elv="true" href="https://www.g2.com/categories/aws-marketplace">G2 reviews in the AWS Marketplace category</a>:</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true"><a class="a a--md" elv="true" href="https://www.g2.com/products/base64-ai-automated-document-data-extraction/reviews"><strong>Base64.ai Automated Document Data Extraction</strong></a> – Specializes in AI-driven document processing. It extracts data from invoices, receipts, and IDs in seconds, reducing manual data entry and improving accuracy. For teams that have used it, how effective is it at handling different document formats at scale?</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true"><a class="a a--md" elv="true" href="https://www.g2.com/products/python/reviews"><strong>Python</strong></a> – While known as a programming language, Python is one of the most important AI enablers on AWS. With libraries like TensorFlow, PyTorch, and Scikit-learn, teams use it to build custom machine learning models. Has anyone used Python on AWS to operationalize AI workloads successfully?</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true"><a class="a a--md" elv="true" href="https://www.g2.com/products/amazon-ec2/reviews"><strong>Amazon EC2</strong></a> – Provides the compute backbone for training and deploying AI models. Its support for GPU instances makes it popular for deep learning. Curious to hear if anyone has leveraged EC2 for cost-effective model training at scale.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true"><a class="a a--md" elv="true" href="https://www.g2.com/products/ubuntu-20-ubuntu-20-04-lts/reviews"><strong>Ubuntu 20.04 LTS</strong></a> – A reliable OS for AI workloads. Many teams choose Ubuntu because it’s compatible with most ML frameworks and works well for containerized deployments. How has it performed for those running AI pipelines in production?</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true"><a class="a a--md" elv="true" href="https://www.g2.com/products/boomi/reviews"><strong>Boomi</strong></a> – Enhances AI workflows by integrating data across applications and platforms. This helps ensure that machine learning models on AWS are trained with accurate, unified data. Has anyone used Boomi to feed cleaner data into their AI pipelines?</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">If your team has worked with any of these—or shifted from one AI solution to another—I’d love to know what influenced your decision. Which features were the most valuable, and how well did they scale with your AI use cases?</p>

##### Post Metadata
- Posted at: 8 months ago
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;From what I’ve seen, &lt;a href=&quot;https://www.g2.com/products/aws-glue/reviews&quot; rel=&quot;noopener noreferrer&quot; target=&quot;_blank&quot;&gt;AWS Glue&lt;/a&gt; is a go-to for teams already building inside AWS, while &lt;a href=&quot;https://www.g2.com/products/azure-data-factory/reviews&quot; rel=&quot;noopener noreferrer&quot; target=&quot;_blank&quot;&gt;Azure Data Factory&lt;/a&gt; seems more popular for hybrid migrations. Has anyone here tried &lt;a href=&quot;https://www.g2.com/products/ibm-streamsets/reviews&quot; rel=&quot;noopener noreferrer&quot; target=&quot;_blank&quot;&gt;IBM StreamSets&lt;/a&gt; to keep migrations continuous instead of one-time lifts?&lt;/p&gt;

##### Comment Metadata
- Posted at: 8 months ago





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