Top 10 ETHoS. Alternatives & Competitors

Top 10 Alternatives to ETHoS. Recently Reviewed By G2 Community

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Google Cloud BigQuery
By Google
4.5/5
(1,235)
Product Description
Analyze Big Data in the cloud with BigQuery. Run fast, SQL-like queries against multi-terabyte datasets in seconds. Scalable and easy to use, BigQuery gives you real-time insights about your data.
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Categories in common with ETHoS.:
Big Data Analytics

MATLAB
By MathWorks
4.5/5
(768)
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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Categories in common with ETHoS.:
Big Data Analytics

Databricks
By Databricks Inc.
4.6/5
(759)
Product Description
Making big data simple
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Categories in common with ETHoS.:
Big Data Analytics

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Alteryx
By Alteryx
4.6/5
(679)
Product Description
Alteryx drives transformational business outcomes through unified analytics, data science, and process automation.
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Categories in common with ETHoS.:
Big Data Analytics

Splunk Enterprise
By Cisco
4.3/5
(431)
Product Description
Splunk is a software platform for machine data that enables customers to gain real-time Operational Intelligence.
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Categories in common with ETHoS.:
Big Data Analytics

Teradata Vantage
By Teradata
4.3/5
(362)
Product Description
The Teradata Database easily and efficiently handles complex data requirements and simplifies management of the data warehouse environment.
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Categories in common with ETHoS.:
Big Data Analytics

Kyvos Semantic Layer
By Kyvos Insights
4.8/5
(270)
Product Description
Kyvos is a semantic layer for AI and BI. It gives enterprises a single, consistent, business-friendly view of their data for trusted AI and BI — eliminating metric drift across BI tools, and grounding AI in governed semantic context for higher accuracy. Kyvos delivers lightning-fast analytics at massive scale and high concurrency, including high-grain multidimensional analytics on the cloud, while reducing cloud spend.
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Categories in common with ETHoS.:
Big Data Analytics

Qubole
By Qubole
4/5
(259)
Product Description
Qubole delivers a Self-Service Platform for Big Data Analytics built on Amazon, Microsoft and Google Clouds
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Categories in common with ETHoS.:
Big Data Analytics

Azure Databricks
By Microsoft
4.5/5
(235)
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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Categories in common with ETHoS.:
Big Data Analytics