Top 10 IBM Cloud Pak for Data Alternatives & Competitors

Top 10 Alternatives to IBM Cloud Pak for Data Recently Reviewed By G2 Community

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Snowflake
By Snowflake, Inc.
4.6/5
(682)
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 IBM Cloud Pak for Data, Snowflake is:
Easier to set up
Easier to admin
More usable
Categories in common with IBM Cloud Pak for Data:
Big Data Analytics
Data Science and Machine Learning Platforms

Databricks
By Databricks Inc.
4.6/5
(657)
Product Description
Making big data simple
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Reviewers say compared to IBM Cloud Pak for Data, Databricks is:
Easier to set up
More usable
Easier to do business with
Categories in common with IBM Cloud Pak for Data:
Big Data Analytics
Data Science and Machine Learning Platforms
Generative AI Infrastructure

Vertex AI
By Google
4.3/5
(650)
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 IBM Cloud Pak for Data, Vertex AI is:
Easier to set up
Easier to admin
More expensive
Categories in common with IBM Cloud Pak for Data:
Data Science and Machine Learning Platforms
Generative AI Infrastructure
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Dataiku
By Dataiku
4.4/5
(188)
Product Description
Dataiku is the Universal AI Platform, giving organizations control over their AI talent, processes, and technologies to unleash the creation of analytics, models, and agents.
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Reviewers say compared to IBM Cloud Pak for Data, Dataiku is:
Easier to set up
More usable
More expensive
Categories in common with IBM Cloud Pak for Data:
Big Data Analytics
Data Science and Machine Learning Platforms
Predictive Analytics
Generative AI Infrastructure

Alteryx
By Alteryx
4.6/5
(669)
Product Description
Alteryx drives transformational business outcomes through unified analytics, data science, and process automation.
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Reviewers say compared to IBM Cloud Pak for Data, Alteryx is:
Easier to set up
Easier to do business with
Easier to admin
Categories in common with IBM Cloud Pak for Data:
Big Data Analytics
Data Science and Machine Learning Platforms
Predictive Analytics

Altair AI Studio
By Altair
4.6/5
(513)
Product Description
RapidMiner is a powerful, easy to use and intuitive graphical user interface for the design of analytic processes. Let the Wisdom of Crowds and recommendations from the RapidMiner community guide your way. And you can easily reuse your R and Python code.
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Reviewers say compared to IBM Cloud Pak for Data, Altair AI Studio is:
Easier to set up
Easier to admin
Easier to do business with
Categories in common with IBM Cloud Pak for Data:
Data Science and Machine Learning Platforms
Predictive Analytics
Generative AI Infrastructure

SAP Analytics Cloud
By SAP
4.2/5
(882)
Product Description
SAP Analytics Cloud is a multi-cloud solution built for software as a service (SaaS) that provides all analytics and planning capabilities – business intelligence (BI), augmented and predictive analytics, and extended planning and analysis – for all users in one offering.
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Reviewers say compared to IBM Cloud Pak for Data, SAP Analytics Cloud is:
Easier to set up
Easier to admin
Easier to do business with
Categories in common with IBM Cloud Pak for Data:
Predictive Analytics

Azure Databricks
By Microsoft
4.5/5
(229)
Product Description
Azure Databricks is a unified, open analytics platform developed collaboratively by Microsoft and Databricks. Built on the lakehouse architecture, it seamlessly integrates data engineering, data science, and machine learning within the Azure ecosystem. This platform simplifies the development and deployment of data-driven applications by providing a collaborative workspace that supports multiple programming languages, including SQL, Python, R, and Scala. By leveraging Azure Databricks, organizations can efficiently process large-scale data, perform advanced analytics, and build AI solutions, all while benefiting from the scalability and security of Azure. Key Features and Functionality: - Lakehouse Architecture: Combines the best elements of data lakes and data warehouses, enabling unified data storage and analytics. - Collaborative Notebooks: Interactive workspaces that support multiple languages, facilitating teamwork among data engineers, data scientists, and analysts. - Optimized Apache Spark Engine: Enhances performance for big data processing tasks, ensuring faster and more reliable analytics. - Delta Lake Integration: Provides ACID transactions and scalable metadata handling, improving data reliability and consistency. - Seamless Azure Integration: Offers native connectivity to Azure services like Power BI, Azure Data Lake Storage, and Azure Synapse Analytics, streamlining data workflows. - Advanced Machine Learning Support: Includes pre-configured environments for machine learning and AI development, with support for popular frameworks and libraries. Primary Value and Solutions Provided: Azure Databricks addresses the challenges of managing and analyzing vast amounts of data by offering a scalable and collaborative platform that unifies data engineering, data science, and machine learning. It simplifies complex data workflows, accelerates time-to-insight, and enables the development of AI-driven solutions. By integrating seamlessly with Azure services, it ensures secure and efficient data processing, helping organizations make data-driven decisions and innovate rapidly.
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Reviewers say compared to IBM Cloud Pak for Data, Azure Databricks is:
Slower to reach roi
Easier to set up
Easier to admin
Categories in common with IBM Cloud Pak for Data:
Big Data Analytics

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 IBM Cloud Pak for Data, MATLAB is:
Slower to reach roi
Easier to set up
Easier to admin
Categories in common with IBM Cloud Pak for Data:
Big Data Analytics
Data Science and Machine Learning Platforms

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