Software Alternatives, Accelerators & Startups

StreamSets Data Collector VS Amazon SageMaker

Compare StreamSets Data Collector VS Amazon SageMaker and see what are their differences

StreamSets Data Collector logo StreamSets Data Collector

The StreamSets Data Collector (SDC) is used to build, test and execute dataflow pipelines for data lake and multi-cloud data movement plus cybersecurity, IoT and customer 360 applications.

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.
  • StreamSets Data Collector Landing page
    Landing page //
    2023-10-20
  • Amazon SageMaker Landing page
    Landing page //
    2023-03-15

StreamSets Data Collector videos

Data Pipeline Preview with StreamSets Data Collector

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 StreamSets Data Collector and Amazon SageMaker)
Stream Processing
100 100%
0% 0
Data Science And Machine Learning
Big Data
100 100%
0% 0
AI
0 0%
100% 100

User comments

Share your experience with using StreamSets Data Collector and Amazon SageMaker. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

StreamSets Data Collector Reviews

We have no reviews of StreamSets Data Collector yet.
Be the first one to post

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 37 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.

StreamSets Data Collector mentions (0)

We have not tracked any mentions of StreamSets Data Collector yet. Tracking of StreamSets Data Collector recommendations started around Mar 2021.

Amazon SageMaker mentions (37)

  • Quantum Convolutional Neural Networks
    Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. - Source: dev.to / 25 days ago
  • 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 / about 2 months 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 / 3 months 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 / 5 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: about 1 year ago
View more

What are some alternatives?

When comparing StreamSets Data Collector and Amazon SageMaker, you can also consider the following products

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

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.

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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.

Spark Streaming - Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.

Deepnote - A collaboration platform for data scientists