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Airtable VS Amazon SageMaker

Compare Airtable VS Amazon SageMaker and see what are their differences

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Airtable logo Airtable

Airtable works like a spreadsheet but gives you the power of a database to organize anything. Sign up for free.

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.
  • Airtable Landing page
    Landing page //
    2023-10-19
  • Amazon SageMaker Landing page
    Landing page //
    2023-03-15

Airtable features and specs

  • User-Friendly Interface
    Airtable provides an intuitive, visually appealing interface that makes it easy for users to create, manage, and navigate complex data sets without extensive technical knowledge.
  • Customizability
    Airtable offers robust customization options, allowing users to tailor databases and views to their specific needs, including various field types, multiple views, and linked records.
  • Collaboration Features
    Airtable supports real-time collaboration, enabling multiple users to work on the same database simultaneously while tracking changes and maintaining version history.
  • Integrations
    Airtable integrates with various third-party applications and services such as Slack, Google Drive, and Zapier, allowing for seamless workflow automation and enhanced productivity.
  • Templates
    Airtable offers a wide range of pre-built templates for different use cases, which helps users get started quickly without having to build everything from scratch.
  • Mobile App
    Airtable's mobile application allows users to access and manage their databases on the go, ensuring flexibility and continuous productivity.

Possible disadvantages of Airtable

  • Cost
    While Airtable offers a free tier, many of the more advanced features and higher usage limits are locked behind a subscription model, which can become costly for larger teams or extensive use.
  • Performance Issues
    Some users have reported performance issues with Airtable when working with very large databases, including slow load times and laggy interface responsiveness.
  • Limited Offline Access
    Airtable relies heavily on an internet connection, and its offline capabilities are limited, which may be a drawback for users who need consistent access without reliable internet.
  • Data Export Options
    Data export options are somewhat limited compared to other database management tools, making it more difficult to extract data in certain formats for use outside of Airtable.
  • Learning Curve
    Despite its user-friendly interface, the extensive features and customizability of Airtable can present a learning curve for new users, requiring time to explore and understand its full capabilities.
  • Lack of Advanced Features
    Airtable may lack some advanced features found in more specialized or traditional database management systems, making it less suitable for particularly complex or highly specific data management needs.

Amazon SageMaker features and specs

  • Fully Managed Service
    Amazon SageMaker is a fully managed service that eliminates the heavy lifting involved with setting up and maintaining infrastructure for machine learning. This allows data scientists and developers to focus on building and deploying machine learning models without worrying about underlying servers or infrastructure.
  • Scalability
    Amazon SageMaker provides scalable resources that can automatically adjust to the needs of your workload, ensuring that you can handle anything from small-scale experimentation to large-scale production deployments.
  • Integrated Development Environment
    SageMaker includes a built-in Jupyter notebook interface, which makes it straightforward for data scientists to write code, visualize data, and run experiments interactively without leaving the platform.
  • Support for Popular Machine Learning Frameworks
    SageMaker supports popular frameworks such as TensorFlow, PyTorch, Apache MXNet, and more. It also provides pre-built algorithms that can be used out-of-the-box, offering flexibility in choosing the right tool for your ML tasks.
  • Automatic Model Tuning
    SageMaker includes hyperparameter tuning capabilities that automate the process of finding the best set of hyperparameters for your model, thus saving significant time and computational resources.
  • Advanced Security Features
    SageMaker integrates with AWS Identity and Access Management (IAM) for fine-grained access control, supports encryption of data at rest and in transit, and complies with various security standards, ensuring that your machine learning projects are secure.
  • Cost Management
    With SageMaker, you only pay for what you use. This pay-as-you-go pricing model allows for better cost management and optimization, making it a cost-effective solution for various machine learning workloads.

Possible disadvantages of Amazon SageMaker

  • Complexity for New Users
    The plethora of features and options available in SageMaker can be overwhelming for beginners who are new to machine learning or the AWS ecosystem. It might require a steep learning curve to become proficient in using the platform effectively.
  • Vendor Lock-In
    Using Amazon SageMaker ties you to the AWS ecosystem, which can be a disadvantage if you want flexibility in switching between different cloud providers. Migrating models and workflows from SageMaker to another platform could be challenging.
  • Cost Management Challenges
    While SageMaker offers a pay-as-you-go pricing model, the costs can quickly add up, especially for large-scale or long-running tasks. It may require diligent monitoring and optimization to avoid unexpectedly high bills.
  • Resource Limitations
    While SageMaker is highly scalable, there are certain resource limits (like instance types and quotas) that might be restrictive for very high-demand or specialized machine learning tasks. These limits could potentially hinder the flexibility you get from an on-premises or custom deployed solution.
  • Integration Complexity
    Integrating SageMaker with other tools and systems within your workflow might require additional development effort. Custom integrations can be complex and could involve additional overhead to set up and maintain.

Airtable videos

+ Add

Airtable API Tutorial With cURL and JavaScript

More videos:

  • Review - Airtable Review | Features, Pricing & Team Use
  • Review - Airtable Blocks for Project Management
  • Review - Airtable vs. Google Sheets
  • Review - airtable review

Amazon SageMaker videos

+ Add

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 Airtable and Amazon SageMaker)

Airtable

Amazon SageMaker

Project Management
100 100%
Project Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
No Code
100 100%
No Code
0% 0
AI
0 0%
AI
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 Airtable and Amazon SageMaker

Airtable Reviews

  1. Sanjana Shah
    · Data Scientist at Boston Institute of Analytics ·
    Airtable: Spreadsheets + Databases = Efficiency

    Airtable is a powerful cloud-based software that combines spreadsheets and databases, offering real-time collaboration and customizable features for efficient task management1.

    🏁 Competitors: monday.com, ClickUp, Smartsheet
    👍 Pros:    Free forever plan and affordable paid options starting at $10 per month.|Visually appealing and user-friendly interface.|Pre-made templates for easy setup and use.|Real-time collaboration and communication.|Customizable features for task management.
    👎 Cons:    Limited project customization without a paid plan.|Top-tier accounts required for gantt tools.|May take time to learn and grasp advanced features.
The Top 7 ClickUp Alternatives You Need to Know in 2025
Benefits:Airtable's ability to integrate various data sources into one platform allows teams to maintain a centralized source of truth while leveraging powerful visualization tools6.
Source: www.ledgerteams.com
Top 10 Notion Alternatives for 2025 and Why Teams Are Choosing Ledger
Airtable blends spreadsheets with database features, offering teams a powerful way to organize structured information. While its flexibility is impressive, it's not purpose-built for communication or team collaboration at scale.
Source: www.ledgerteams.com
25 Best Asana Alternatives & Competitors for Project Management in 2024
Airtable is one of the most popular Asana alternatives. It’s project management tool that helps teams create detailed databases for their work. Users can group and sort data in custom fields with views like Grid to include only the relevant project information.
Source: clickup.com
Top 10 Microsoft Power Apps Alternatives and Competitors 2024
Airtable Pricing: Airtable offers a freemium plan with limited features for individual users. Paid plans start at $10 per user per month for additional features and functionalities. Enterprise plans with custom pricing cater to large-scale deployments.
Source: medium.com
The 10 best Asana alternatives in 2024
If you're looking for a project management app that leans more toward data management, try Airtable. Out of the box, Airtable's default view looks like a spreadsheet. It offers a few project templates based on your team type (such as marketing or sales), or you can build a "base" from scratch. From there, you can add highly customizable fields (or columns) to each row, so...
Source: zapier.com

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, Airtable should be more popular than Amazon SageMaker. It has been mentiond 130 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.

Airtable mentions (130)

  • How to Build Internal Tools 100x Faster
    It is possible to speed up the development and delivery process for many internal applications by using no-code or low code tools. These vary in offerings from open source to SaaS, including popular ones like AirTable, BudiBase, Retool, NocoDB and others. These can all greatly help speed up delivery times. - Source: dev.to / 5 months ago
  • Growing a side-project to 100k Unique Visitors in one week
    For the backend, I opted for Airtable as a database. It's a simple, no-code solution that I've used before. It's not the most powerful database, but it's perfect for a project like this. I could easily add, edit, and delete records, and it has an embeddable form functionality that I used for user submissions. - Source: dev.to / about 1 year ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Airtable.com — Looks like a spreadsheet, but it's a relational database unlimited bases, 1,200 rows/base, and 1,000 API requests/month. - Source: dev.to / about 1 year ago
  • How to generate links to a record to view it in an Interface?
    The ?XXXXX part of the URL identifies the type of interface page it is. Just copy that and then your formula is just "https://airtable.com.../...?XXXXXX=" & RECORD_ID() I'm not sure it works in every type of interface page (where you've started from a blank page for example). There has to be something to identify the record viewed from the page, if you see what I mean. Source: over 1 year ago
  • Working on a personal app for data tracking. looking for suggestions
    So I started building something on airtable.com that would allow me to easily track updates for each batch. What in your experience would make sense to track that I may be missing? Source: over 1 year ago
View more

Amazon SageMaker mentions (44)

  • Dashboard for Researchers & Geneticists: Functional Requirements [System Design]
    Leverage Amazon SageMaker: For machine learning (ML) tasks, users can leverage Amazon SageMaker to analyze large datasets and build predictive models. - Source: dev.to / 15 days ago
  • Address Common Machine Learning Challenges With Managed MLflow
    MLflow, an Apache 2.0-licensed open-source platform, addresses these issues by providing tools and APIs for tracking experiments, logging parameters, recording metrics and managing model versions. It also helps to address common machine learning challenges, including efficiently tracking, managing, deploying ML models and enhancing workflows across different ML tasks. Amazon SageMaker with MLflow offers secure... - Source: dev.to / about 2 months ago
  • How I suffered my first burnout as software developer
    Our first task for the client was to evaluate various MLOps solutions available on the market. Over the summer of 2022, we conducted small proofs-of-concept with platforms like Amazon SageMaker, Iguazio (the developer of MLRun), and Valohai. However, because we weren’t collaborating directly with the teams we were supposed to support, these proofs-of-concept were limited. Instead of using real datasets or models... - Source: dev.to / 4 months ago
  • 👋🏻Goodbye Power BI! 📊 In 2025 Build AI/ML Dashboards Entirely Within Python 🤖
    Taipy’s ecosystem doesn’t stop at dashboards. With Taipy you can orchestrate data workflows and create advanced user interfaces. Besides, the platform supports every stage of building enterprise-grade applications. Additionally, Taipy’s integration with leading platforms such as Databricks, Snowflake, IBM WatsonX, and Amazon SageMaker ensures compatibility with your existing data infrastructure. - Source: dev.to / 5 months ago
  • Understanding the MLOps Lifecycle
    Based on your technological stack, various services are used to deploy machine learning models. Some popular services are AWS Sagemaker, Azure Machine Learning, Vertex AI, and many others. - Source: dev.to / 5 months ago
View more

What are some alternatives?

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

Asana - Asana project management is an effort to re-imagine how we work together, through modern productivity software. Fast and versatile, Asana helps individuals and groups get more done.

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.

Trello - Infinitely flexible. Incredibly easy to use. Great mobile apps. It's free. Trello keeps track of everything, from the big picture to the minute details.

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.

Basecamp - A simple and elegant project management system.

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

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