Top 10 Azure Data Lake Analytics Alternatives & Competitors

Top 10 Alternatives to Azure Data Lake Analytics Recently Reviewed By G2 Community

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Google Cloud BigQuery
By Google
4.5/5
(1,226)
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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Reviewers say compared to Azure Data Lake Analytics, Google Cloud BigQuery is:
Easier to set up
More usable
Better at meeting requirements
Categories in common with Azure Data Lake Analytics:
Big Data Analytics

Splunk Enterprise
By Cisco
4.3/5
(433)
Product Description
Splunk is a software platform for machine data that enables customers to gain real-time Operational Intelligence.
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Reviewers say compared to Azure Data Lake Analytics, Splunk Enterprise is:
More expensive
Better at meeting requirements
Easier to do business with
Categories in common with Azure Data Lake Analytics:
Big Data Analytics

Snowflake
By Snowflake, Inc.
4.5/5
(755)
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 Azure Data Lake Analytics, Snowflake is:
More usable
Easier to set up
Better at meeting requirements
Categories in common with Azure Data Lake Analytics:
Big Data Analytics

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MATLAB
By MathWorks
4.5/5
(771)
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 Azure Data Lake Analytics, MATLAB is:
More expensive
Better at meeting requirements
Easier to set up
Categories in common with Azure Data Lake Analytics:
Big Data Analytics

Teradata Autonomous Knowledge Platform
By Teradata Autonomous Knowledge Platform
4.3/5
(375)
Product Description
Teradata Autonomous Knowledge Platform easily and efficiently handles complex data requirements and simplifies management of the data warehouse environment.
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Reviewers say compared to Azure Data Lake Analytics, Teradata Autonomous Knowledge Platform is:
More expensive
Better at meeting requirements
Categories in common with Azure Data Lake Analytics:
Big Data Analytics

Alteryx
By Alteryx
4.6/5
(817)
Product Description
Alteryx drives transformational business outcomes through unified analytics, data science, and process automation.
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Reviewers say compared to Azure Data Lake Analytics, Alteryx is:
More expensive
More usable
Easier to do business with
Categories in common with Azure Data Lake Analytics:
Big Data Analytics

Kyvos Semantic Layer
By Kyvos Insights
4.8/5
(281)
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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Reviewers say compared to Azure Data Lake Analytics, Kyvos Semantic Layer is:
Better at support
Easier to set up
More usable
Categories in common with Azure Data Lake Analytics:
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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Reviewers say compared to Azure Data Lake Analytics, Qubole is:
More expensive
Categories in common with Azure Data Lake Analytics:
Big Data Analytics

dbt
By dbt Labs
4.7/5
(208)
Product Description
dbt is a transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.
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Reviewers say compared to Azure Data Lake Analytics, dbt is:
More usable
Better at meeting requirements
Better at support
Categories in common with Azure Data Lake Analytics:
Big Data Analytics