Software Alternatives, Accelerators & Startups
Register | Login

Amazon SageMaker VS Wasabi Cloud Object Storage

Compare Amazon SageMaker VS Wasabi Cloud Object Storage and see what are their differences

Electe
Discover Electe, our data analytics platform dedicated to SMEs. Don't let your data go unused, take your business into the future! featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

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.

Wasabi Cloud Object Storage logo Wasabi Cloud Object Storage

Storage made simple. Faster than Amazon's S3. Less expensive than Glacier.
  • Amazon SageMaker Landing page
    Landing page //
    2023-03-15
  • Wasabi Cloud Object Storage Landing page
    Landing page //
    2025-04-16

Wasabi Hot Cloud Storage is a scalable, cloud-based object storage service for various applications. It allows storing any type of data in any format, offering high-performance, reliability, and security at a minimal cost. Ideal for individuals and organizations seeking affordable, dependable data storage, Wasabi provides a highly durable and fault-tolerant infrastructure, ensuring data is always accessible and protected. With features like immutable buckets, versioning, and encryption, Wasabi ensures data integrity and security, making it a trusted choice for businesses and individuals alike.

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.

Wasabi Cloud Object Storage features and specs

  • Cost-Effective
    Wasabi offers competitive pricing for cloud storage without any hidden fees, making it a cost-effective option for businesses of all sizes.
  • High Performance
    Wasabi provides high-speed data retrieval and upload, which is ideal for applications requiring fast access to stored data.
  • Simple Pricing Model
    There are no fees for egress or API requests, which simplifies budgeting and cost management.
  • Scalability
    Wasabi's storage solutions can scale to meet the needs of growing businesses, providing flexibility as data storage requirements increase.
  • Security
    Wasabi offers strong security features, including data encryption both in transit and at rest, ensuring the safety of stored data.
  • S3 Compatibility
    Wasabi's storage service is compatible with the Amazon S3 API, making it easier for users to integrate with existing tools and workflows.

Possible disadvantages of Wasabi Cloud Object Storage

  • Limited Services
    Compared to larger cloud providers like AWS or Google Cloud, Wasabi focuses primarily on storage and offers fewer ancillary services and features.
  • Geographical Availability
    Wasabi has fewer data center locations worldwide compared to major competitors, which might impact performance for users in certain regions.
  • Customer Support
    While Wasabi offers customer support, it may not be as comprehensive or as responsive as the support provided by larger cloud service providers.
  • Ecosystem Integration
    Although it supports S3 compatibility, Wasabi might not integrate as seamlessly with other cloud ecosystem services beyond storage.
  • No Free Tier
    Unlike some competitors, Wasabi does not offer a free tier for basic storage needs, which could be a drawback for small businesses or startups.

Analysis of Wasabi Cloud Object Storage

Overall verdict

  • Wasabi Cloud Object Storage is a strong option for businesses looking for affordable and easy-to-use cloud storage. Its predictable pricing and robust performance make it particularly attractive for organizations that require frequent data access or those with fluctuating storage needs.

Why this product is good

  • Wasabi Cloud Object Storage is often praised for its affordability and simplicity compared to other cloud storage providers. It offers a flat-rate pricing model without egress fees, making it cost-effective for businesses that need to frequently access their data. Wasabi is also recognized for its high-speed performance and data integrity features, such as eleven nines of durability and immutability options to protect against accidental or malicious data deletion.

Recommended for

  • Businesses seeking cost-effective cloud storage without unexpected charges.
  • Organizations that need to frequently access or transfer large volumes of data.
  • Companies requiring secure data storage with features like data immutability and high durability.
  • Users looking for a straightforward alternative to more complex storage solutions.

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)

Wasabi Cloud Object Storage videos

+ Add

Introduction to Wasabi Hot Cloud Storage

More videos:

  • Review - Introduction to Wasabi Hot Cloud Storage (August 2021) | Wasabi

Category Popularity

0-100% (relative to Amazon SageMaker and Wasabi Cloud Object Storage)

Amazon SageMaker

Wasabi Cloud Object Storage

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Cloud Storage
0 0%
Cloud Storage
100% 100
AI
100 100%
AI
0% 0
Cloud Computing
0 0%
Cloud Computing
100% 100

User comments

Share your experience with using Amazon SageMaker and Wasabi Cloud Object Storage. 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 Amazon SageMaker and Wasabi Cloud Object Storage

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

Wasabi Cloud Object Storage Reviews

7 Best Amazon S3 Alternatives & Competitors in 2024
Wasabi hot storage differentiates itself against industry giants like Amazon S3 by offering storage that’s six times faster and up to 80% cheaper.
Source: diggitymarketing.com
Wasabi, Storj, Backblaze et al, are promising 80%+ savings compared to Amazon S3... What's the catch?
On the surface, Wasabi looks appealing with a simple pricing structure ($5.99/TB/mo) that comes with free egress and free operations. How can Wasabi afford this, you ask? Well, their business model relies on their user-base keeping their data stored (and unchanged) for some time and not consuming more than their fair share of resources, which they regulate via a handful of...
Source: dev.to

Social recommendations and mentions

Based on our record, Wasabi Cloud Object Storage should be more popular than Amazon SageMaker. It has been mentiond 70 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.

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 / about 1 month 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 / 3 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 / 5 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 / 6 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 / 6 months ago
View more

Wasabi Cloud Object Storage mentions (70)

  • Using ColdFusion to Generate Pre-Signed Wasabi Download URL
    There was an internal decision to use Wasabi Cloud Storage instead of Amazon S3 and I needed to use ColdFusion to generate a pre-signed URL to allow access to AI-generated content for a limited time. I had used the Sv4Util.cfc and aws-cfml libraries before with Amazon and thought it was just as simple, but I got confused somewhere along the way and it just wasn't working. - Source: dev.to / 2 months ago
  • How much 1 TB of egress costs by cloud provider
    This table is missing Wasabi [0], which has free egress. [0]: https://wasabi.com. - Source: Hacker News / over 1 year ago
  • What makes backblaze better than some of the other options out there?
    Backblaze is great because it's a set price, unlimited, and I don't have to think twice about it. I use Arq to backup my machine + external drives (several drives with lots of photos) to my local NAS. Was sending data to Wasabi, but the costs got out of control. I can purchase a year's worth of Backblaze + the 1 year revision upgrade for much, much less of what I was paying at Wasabi. Source: almost 2 years ago
  • The NixOS Foundation’s Call to Action: S3 Costs Require Community Support
    What about looking at Wasabi? It’s $5.99 per TB per month https://wasabi.com. - Source: Hacker News / almost 2 years ago
  • A web application that will need to store lots of image files. The company wants to use Dropbox for image storage. Is this okay?
    No, use AWS S3 or https://wasabi.com/ if you are worried about cost. Source: about 2 years ago
View more

What are some alternatives?

When comparing Amazon SageMaker and Wasabi Cloud Object Storage, you can also consider the following products

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.

Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.

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.

Contabo Object Storage - S3-compatible cloud object storage with unlimited, free transfer at a fraction of what others charge. Easy migration & predictable billing. Sign up now & save.

Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.

Hetzner Object Storage - Scalable object storage, S3-compatible and ideal for growing data volumes. Secure and flexible for efficient data storage.

Loading...