Top 10 Dataloop Alternatives & Competitors

Top 10 Alternatives to Dataloop Recently Reviewed By G2 Community

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SuperAnnotate
By SuperAnnotate
4.9/5
(288)
Product Description
SuperAnnotate is the leading platform for building, fine-tuning, iterating, and managing your AI models faster with the highest-quality training data.
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Reviewers say compared to Dataloop, SuperAnnotate is:
Easier to do business with
Easier to set up
Better at meeting requirements
Categories in common with Dataloop:
Active Learning Tools
Data Labeling
MLOps Platforms

Labelbox
By Labelbox
4.5/5
(47)
Product Description
A complete training data platform for AI.
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Reviewers say compared to Dataloop, Labelbox is:
Easier to set up
Better at meeting requirements
More usable
Categories in common with Dataloop:
Active Learning Tools
Data Labeling
MLOps Platforms
Data Science and Machine Learning Platforms

V7 Darwin
By V7
4.8/5
(54)
Product Description
V7 Darwin is a data labeling platform used by AI developers who need to train specialized computer vision models. It supports diverse data types, including images, videos, and medical imaging formats like DICOM or WSI. The platform offers AI-assisted labeling, data management, and workflow orchestration tools to help companies, clinics, and research labs create high-quality training data for building sophisticated AI solutions. It is especially useful for managing complex review processes and real-time collaboration between multiple teams of annotators, engineers, and domain experts. V7 Darwin integrates with popular ML frameworks and infrastructure and maintains high security and compliance standards (SOC 2, HIPAA), which makes it suitable for industries such as healthcare, retail, security, and manufacturing.
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Reviewers say compared to Dataloop, V7 Darwin is:
Slower to reach roi
Easier to do business with
Easier to set up
Categories in common with Dataloop:
Data Labeling
MLOps Platforms

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Databricks
By Databricks Inc.
4.6/5
(731)
Product Description
Making big data simple
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Reviewers say compared to Dataloop, Databricks is:
More expensive
Better at meeting requirements
Easier to set up
Categories in common with Dataloop:
MLOps Platforms
Data Science and Machine Learning Platforms

Vertex AI
By Google
4.3/5
(652)
Product Description
Vertex AI is a managed machine learning (ML) platform that helps you build, train, and deploy ML models faster and easier. It includes a unified UI for the entire ML workflow, as well as a variety of tools and services to help you with every step of the process. Vertex AI Workbench is a cloud-based IDE that is included with Vertex AI. It makes it easy to develop and debug ML code. It provides a variety of features to help you with your ML workflow, such as code completion, linting, and debugging. Vertex AI and Vertex AI Workbench are a powerful combination that can help you accelerate your ML development. With Vertex AI, you can focus on building and training your models, while Vertex AI Workbench takes care of the rest. This frees you up to be more productive and creative, and it helps you get your models into production faster. If you're looking for a powerful and easy-to-use ML platform, then Vertex AI is a great option. With Vertex AI, you can build, train, and deploy ML models faster and easier than ever before.
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Reviewers say compared to Dataloop, Vertex AI is:
More expensive
Categories in common with Dataloop:
MLOps Platforms
Data Science and Machine Learning Platforms

SAP HANA Cloud
By SAP
4.3/5
(595)
Product Description
SAP HANA Cloud is the cloud-native data foundation of SAP Business Technology Platform, it stores, processes and analyzes data in real time at petabyte scale and converges multiple data types in a single system while managing it more efficiently with integrated multitier storage.
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Reviewers say compared to Dataloop, SAP HANA Cloud is:
Slower to reach roi
More expensive
Categories in common with Dataloop:
MLOps Platforms
Data Science and Machine Learning Platforms

MATLAB
By MathWorks
4.5/5
(765)
Product Description
MATLAB is a high-level programming and numeric computing environment widely utilized by engineers and scientists for data analysis, algorithm development, and system modeling. It offers a desktop environment optimized for iterative analysis and design processes, coupled with a programming language that directly expresses matrix and array mathematics. The Live Editor feature enables users to create scripts that integrate code, output, and formatted text within an executable notebook. Key Features and Functionality: - Data Analysis: Tools for exploring, modeling, and analyzing data. - Graphics: Functions for visualizing and exploring data through various plots and charts. - Programming: Capabilities to create scripts, functions, and classes for customized workflows. - App Building: Facilities to develop desktop and web applications. - External Language Interfaces: Integration with languages such as Python, C/C++, Fortran, and Java. - Hardware Connectivity: Support for connecting MATLAB to various hardware platforms. - Parallel Computing: Ability to perform large-scale computations and parallelize simulations using multicore desktops, GPUs, clusters, and cloud resources. - Deployment: Options to share MATLAB programs and deploy them to enterprise applications, embedded devices, and cloud environments. Primary Value and User Solutions: MATLAB streamlines complex mathematical computations and data analysis tasks, enabling users to develop algorithms and models efficiently. Its comprehensive toolboxes and interactive apps facilitate rapid prototyping and iterative design, reducing development time. The platform's scalability allows for seamless transition from research to production, supporting deployment on various systems without extensive code modifications. By integrating with multiple programming languages and hardware platforms, MATLAB provides a versatile environment that addresses the diverse needs of engineers and scientists across industries.
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Reviewers say compared to Dataloop, MATLAB is:
Slower to reach roi
Better at meeting requirements
More expensive
Categories in common with Dataloop:
Data Science and Machine Learning Platforms

SAS Viya
By SAS Institute Inc.
4.3/5
(732)
Product Description
As a cloud-native AI, analytics and data management platform, SAS Viya enables you to scale cost-effectively, increase productivity and innovate faster, backed by trust and transparency. SAS Viya makes it possible to integrate teams and technology enabling all users to work together successfully to turn critical questions into accurate decisions.
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Reviewers say compared to Dataloop, SAS Viya is:
Slower to reach roi
Categories in common with Dataloop:
MLOps Platforms
Data Science and Machine Learning Platforms

Snowflake
By Snowflake, Inc.
4.6/5
(697)
Product Description
Snowflake’s platform eliminates data silos and simplifies architectures, so organizations can get more value from their data. The platform is designed as a single, unified product with automations that reduce complexity and help ensure everything “just works”. To support a wide range of workloads, it’s optimized for performance at scale no matter whether someone’s working with SQL, Python, or other languages. And it’s globally connected so organizations can securely access the most relevant content across clouds and regions, with one consistent experience.
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Reviewers say compared to Dataloop, Snowflake is:
Better at meeting requirements
Easier to set up
More usable
Categories in common with Dataloop:
MLOps Platforms
Data Science and Machine Learning Platforms