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Azure Databricks VS StatSoft Statistica

Compare Azure Databricks VS StatSoft Statistica and see what are their differences

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  4. » Alternatives

Azure Databricks logo Azure Databricks

Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

StatSoft Statistica logo StatSoft Statistica

StatSoft Statistica is a highly comprehensive data management suite for dealing with a large set of data and getting the statistical analysis of that data.
  • Azure Databricks Landing page
    Landing page //
    2023-04-02
  • StatSoft Statistica Landing page
    Landing page //
    2023-07-26

Azure Databricks features and specs

  • Scalability
    Azure Databricks enables easy scaling of workloads up or down, allowing users to handle large volumes of data and perform distributed processing efficiently.
  • Integration
    Seamlessly integrates with other Azure services, such as Azure Data Lake Storage and Azure SQL Data Warehouse, facilitating a streamlined data pipeline.
  • Collaboration
    Offers collaborative features like notebooks that allow multiple users to work together easily on data analytics projects.
  • Performance Optimization
    Built on top of Apache Spark, Azure Databricks provides high performance and optimized execution for data engineering and machine learning tasks.
  • Managed Service
    As a fully managed service, it handles infrastructure provisioning and maintenance, enabling users to focus on data insights rather than backend management.

Possible disadvantages of Azure Databricks

  • Cost
    Azure Databricks can be expensive, particularly for large-scale and long-running workloads, which may be a concern for budget-conscious organizations.
  • Complexity
    Despite its capabilities, Azure Databricks may have a steep learning curve, especially for users not familiar with Apache Spark.
  • Vendor Lock-in
    Leveraging Azure-specific services can lead to vendor lock-in, making it challenging to migrate workloads and data to other cloud platforms.
  • Limited Offline Capabilities
    As a cloud-native service, it requires an active internet connection and might not suit scenarios that require offline processing.
  • Compliance Concerns
    Due to Azure Databricks' integration with Azure, users need to carefully manage compliance and data governance, which might be complex in multi-regional deployments.

StatSoft Statistica features and specs

No features have been listed yet.

Azure Databricks videos

+ Add

Azure Databricks is Easier Than You Think

More videos:

  • Review - Ingest, prepare & transform using Azure Databricks & Data Factory | Azure Friday
  • Review - Azure Databricks - What's new! | DB102

StatSoft Statistica videos

No StatSoft Statistica videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Azure Databricks and StatSoft Statistica)

Azure Databricks

StatSoft Statistica

Technical Computing
83 83%
Technical Computing
17% 17
Office & Productivity
100 100%
Office & Productivity
0% 0
Business & Commerce
79 79%
Business & Commerce
21% 21
Statistics
0 0%
Statistics
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Azure Databricks and StatSoft Statistica

Azure Databricks Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Azure Databricks is a data analytics tool optimized for Microsoft’s Azure cloud services solution. It provides three development environments for data-intensive apps, namely Databricks SQL, Databricks Machine Learning, and Databricks Data Science & Engineering.The platform supports languages including Python, Java, R, Scala, and SQL, plus data science frameworks and...
Source: theqalead.com

StatSoft Statistica Reviews

We have no reviews of StatSoft Statistica yet.
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Social recommendations and mentions

Based on our record, Azure Databricks seems to be more popular. It has been mentiond 2 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.

Azure Databricks mentions (2)

  • Top 30 Microsoft Azure Services
    In the big data space, Azure offers Azure Databricks. This is an Apache Spark big data analytics and machine learning service over a Distributed File System. The distributed cluster of nodes running analytics and AI operations in parallel allow for fast processing of large volumes of data and integration with popular machine learning libraries such as PyTorch unleash endless possibilities for custom ML. - Source: dev.to / almost 4 years ago
  • ZooKeeper-free Kafka is out. First Demo
    https://azure.microsoft.com/en-us/services/databricks. - Source: Hacker News / about 4 years ago

StatSoft Statistica mentions (0)

We have not tracked any mentions of StatSoft Statistica yet. Tracking of StatSoft Statistica recommendations started around Mar 2021.

What are some alternatives?

When comparing Azure Databricks and StatSoft Statistica, you can also consider the following products

IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.

IBM SPSS Statistics - IBM SPSS Statistics is software that provides detailed analysis of statistical data. The company behind the product practically needs no introduction, as it's been a staple of the technology industry for over 100 years.

MicroStrategy - MicroStrategy is a cloud-based platform providing business intelligence, mobile intelligence and network applications.

R Lang - R is a free software environment for statistical computing and graphics.

MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

GraphPad Prism - Overview. GraphPad Prism, available for both Windows and Mac computers, combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization.

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