Software Alternatives & Reviews

Diyotta VS Amazon SageMaker

Compare Diyotta VS Amazon SageMaker and see what are their differences

Diyotta logo Diyotta

Enterprise Data Integration For All.

Amazon SageMaker logo Amazon SageMaker

Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
  • Diyotta Landing page
    Landing page //
    2021-10-26

Diyotta is an enterprise-class data integration platform that connects enterprises to all their data. It provides a single integrated platform that makes it easy to quickly and efficiently integrate enormous volumes of data from any source to any target, whether on-premises, in the cloud, or a hybrid environment. Diyotta is built for modern data architectures where data can be processed in batch, or real-time streams, in the most optimized fashion. It also scales in all dimensions with its agent-based architecture and optimizes the data movement across several data-points easily and efficiently.

Diyotta accelerates time to value for new investments in big data platforms and ongoing modernization of data warehouses. With Diyotta, companies fully leverage their existing platform investment, move to modern data platforms with the highest level of reuse possible, and quickly respond to business needs for new data and analytics.

  • Amazon SageMaker Landing page
    Landing page //
    2023-03-15

Diyotta

$ Details
Free Trial $100.0 / Monthly (100 Credits)
Release Date
2011 October

Diyotta videos

CloudSync Product Demo

More videos:

  • Review - Customer Testimonial - Clearsense
  • Tutorial - Data Pipelines In Minutes Using Data Movement Wizard
  • Review - ELT using Diyotta
  • Review - Diyotta | Leading The Modern Data Integration Movement

Amazon SageMaker videos

Build, Train and Deploy Machine Learning Models on AWS with Amazon SageMaker - AWS Online Tech Talks

More videos:

  • Review - An overview of Amazon SageMaker (November 2017)

Category Popularity

0-100% (relative to Diyotta and Amazon SageMaker)
Development
38 38%
62% 62
Data Science And Machine Learning
Backup & Sync
100 100%
0% 0
AI
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Diyotta and Amazon SageMaker

Diyotta Reviews

The 28 Best Data Integration Tools and Software for 2020
Description: Diyotta is a unified data integration platform that integrates with modern data lake and data warehousing environments. The drag-and-drop user interface and native processing capabilities make this product one to consider. Diyotta enables shorter development times, faster data movement, and reusability across the enterprise to make future development simple....

Amazon SageMaker Reviews

7 best Colab alternatives in 2023
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning. It allows users to write code, track experiments, visualize data, and perform debugging and monitoring all within a single, integrated visual interface, making the process of developing, testing, and deploying models much more manageable.
Source: deepnote.com

Social recommendations and mentions

Based on our record, Amazon SageMaker seems to be more popular. It has been mentiond 36 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Diyotta mentions (0)

We have not tracked any mentions of Diyotta yet. Tracking of Diyotta recommendations started around Mar 2021.

Amazon SageMaker mentions (36)

  • Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations
    Damn straight. Oh, wait, some vendors have claimed to build an end-to-end solution. But, meh, that’s marketing talk. Take, for example, a well-known platform like Amazon Sagemaker, which describes itself as “a fully managed service that brings together a broad set of tools to enable high-performance, low-cost machine learning (ML) for any use case.” It’s a great platform. My startup has even partnered with them.... - Source: dev.to / 7 days ago
  • Sentiment Analysis with PubNub Functions and HuggingFace
    At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / 29 days ago
  • Beginning the Journey into ML, AI and GenAI on AWS
    Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 3 months ago
  • Technical Architecture for LLMOps
    Amazon and Azure already have much of what you're talking about in AWS SageMaker and Azure MLOps. Source: 11 months ago
  • Are AI fine-tuning tools worth learning and investing?
    And there have been several platforms that help fine-tune pretrained models, such as Google Cloud AutoML and Amazon Sagemaker. These tools are often fairly easy to use, but they come at a cost. They can be expensive, depending on the size of your dataset. Another option is Finetuner+, that also fine-tunes like AutoML and Sagemaker. The big advantage is that you don't need to transfer your data to other GPUs,... Source: about 1 year ago
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What are some alternatives?

When comparing Diyotta and Amazon SageMaker, you can also consider the following products

Striim - Striim provides an end-to-end, real-time data integration and streaming analytics platform.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

HVR - Your data. Where you need it. HVR is the leading independent real-time data replication solution that offers efficient data integration for cloud and more.

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

Celigo Data Loader - Celigo is an advanced platform that comes with exclusive service data loading in a smooth and effective way.

Azure Machine Learning Studio - Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.