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Microsoft Azure Synapse Analytics vs Oracle Big Data Appliance comparison

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Comparison Buyer's Guide
Executive Summary

We performed a comparison between Microsoft Azure Synapse Analytics and Oracle Big Data Appliance based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Microsoft Azure Synapse Analytics vs. Oracle Big Data Appliance report (Updated: September 2022).
632,611 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The solution operates like a typical SQL Server environment so there is no alienation in terms of technical knowledge.""The integrated workspace in Microsoft Azure Synapse Analytics where everything comes together, such as Power BI and Data Factory, is very good. Additionally, the ability to do dedicated SQL pooling is a benefit.""The architecture, including compute and storage, is good.""What I found most valuable in Microsoft Azure Synapse Analytics is that it's native only for Azure, so you get better performance and there's no issue. To explain further, many different types of data come, in particular, structured and unstructured data. For audit purposes, there's also unstructured data, so the most important aspect is that with Microsoft Azure Synapse Analytics, you have the capability of using both technologies, meaning that you can use or mix structured and unstructured data which is important. This can also be done in Hadoop, and on other platforms, so you have everything in one place. You don't have to worry about how to manage both structured and unstructured data and where to store information. With Microsoft Azure Synapse Analytics, you can take care of everything, particularly in Azure. The solution also provides you with many features apart from analytics, for example, storage which makes it better.""I like SQL post, which is for storage and distributed computing. Another good feature is the copy activity.""Fills the gap between big data and classic data warehouses.""The solution has been working well overall.""It's user-friendly and has a good dashboard."

More Microsoft Azure Synapse Analytics Pros →

"Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard."

More Oracle Big Data Appliance Pros →

Cons
"Indicating what areas need improvement in this solution is a difficult question because the organizations that I am working for are really new in this area. However, an even better more simple interface, or perhaps an extension of a connector app store solution, would be helpful.""Microsoft Azure Synapse Analytics can improve by increasing the size of the files that we can load on the platform. We have some files that are too large to be loaded and it would be a benefit to us if the limit was increased. Additionally, the way we use the tool for generating reports can be made better. They should add some drag-and-drop rules without the need of programming these rules using some programming language. It would be helpful if we did not need someone that was technically advanced to be able to do it with, such as someone with no IT background. Having a reporting tool without code would be great.""The performance and data consistency need to be improved.""The filing can be improved.""We'd, of course, always like to pay less for the service if we can.""Scaling this solution up and down is not quick and easy. This could be improved. The pricing of this solution could also be improved.""It could be more stable.""I am pretty sure that there are areas that need improvement but I just can think of them off the top of my head."

More Microsoft Azure Synapse Analytics Cons →

"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."

More Oracle Big Data Appliance Cons →

Pricing and Cost Advice
  • "Its price could be better. It was a school project, and I got it for free. If I try to pay through my company, it is a little bit more expensive as compared to Oracle."
  • "The price of the package not expensive and depends on how much it is used."
  • "The cost of the licensing depends on the size of the warehouse, where the cost of storage is approximately $130 USD per terabyte."
  • "This is a cost-effective product."
  • "Because it's cloud the cost is a different convention and the licensing costs are not the same."
  • "It's very difficult to price unless you know exactly how the customer is using it."
  • "We normally pay between $300 and $500 per month, which is quite expensive for how much we actually use it, performance- and usage-wise. They have a cheap version and an expensive version, and our usage usually falls in the middle ground, which makes it not as cost-effective as it could be."
  • "The solution is subscription-based. You can also pay to use the product as you go."
  • More Microsoft Azure Synapse Analytics Pricing and Cost Advice →

  • "Oracle's prices are too high compared to others in the market."
  • More Oracle Big Data Appliance Pricing and Cost Advice →

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    Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
    632,611 professionals have used our research since 2012.
    Questions from the Community
    Top Answer:Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different… more »
    Top Answer:Traditional ETL would usually use a dedicated database (or even database server) where you'll load & transform your raw data before ingesting it into the final destination. This would allow checking… more »
    Top Answer:The most valuable feature of Microsoft Azure Synapse Analytics is the capabilities, and the integration with other Azure resources, such as Data Factory, Databricks, and Spark for data processing. The… more »
    Top Answer:Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard.
    Top Answer:From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera. Oracle could also improve Big Data… more »
    Top Answer:I use Big Data Appliance to have a single source of truth for my data and to keep all my data in one place.
    Ranking
    2nd
    Views
    33,974
    Comparisons
    22,792
    Reviews
    45
    Average Words per Review
    484
    Rating
    7.9
    13th
    out of 30 in Data Warehouse
    Views
    1,212
    Comparisons
    1,044
    Reviews
    1
    Average Words per Review
    235
    Rating
    8.0
    Comparisons
    Also Known As
    Azure Synapse Analytics, Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL DW, Azure SQL Data Warehouse, MS Azure Synapse Analytics
    Learn More
    Overview

    Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.

    Microsoft Azure Synapse Analytics is built with these 4 components:

    1. Synapse SQL
    2. Spark
    3. Synapse Pipeline
    4. Studio

    Microsoft Azure Synapse Analytics Features

    Microsoft Azure Synapse Analytics has many valuable key features, including:

    • Cloud Data Service: WIth Microsoft Azure Synapse Analytics you can operate services (data analytics, machine learning, data warehousing, dashboarding, etc.) in a single workspace via the cloud.

    • Structured and unstructured data: Microsoft Azure Synapse Analytics supports both structured and unstructured data and allows you to manage relational and non-relational data - unlike data warehouses and lakes that tend to store them respectively.

    • Effective data storage: Microsoft Azure Synapse Analytics offers next-level data storage with high availability and different tiers.

    • Responsive data engine: Microsoft Azure Synapse Analytics uses Massive Parallel Processing (MPP) and is designed to handle large volumes of data and analytical workloads efficiently without any problems.

    • Several scripting languages: The solution provides language compatibility and supports different programming languages, such as Python, Java, Spark SQL, and Scala.

    • Query optimization: Microsoft Azure Synapse Analytics works well to facilitate limitless concurrency and performance optimization. It also simplifies workload management.

    Microsoft Azure Synapse Analytics Benefits

    Some of the benefits of using Microsoft Azure Synapse Analytics include:

    • Database templates: Microsoft Azure Synapse Analytics offers industry-specific database templates that make it easy to combine and shape data.

    • Better business insights: With Microsoft Azure Synapse Analytics you can expand discovery of insights from all your data and apply machine learning models to all your intelligent apps.

    • Reduce project development time: Microsoft Azure Synapse Analytics makes it possible to have a unified experience for developing end-to-end analytics, which reduces project development time significantly.

    • Eliminate data barriers: By using Microsoft Azure Synapse Analytics, you can perform analytics on operational and business apps data without data movement.

    • Advanced security: Microsoft Azure Synapse Analytics provides both advanced security and privacy features to ensure data protection.

    • Machine Learning: Microsoft Azure Synapse Analytics integrates Azure Machine Learning, Azure Cognitive Services, and Power BI.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.

    PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud."

    Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."

    A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."


    Oracle Big Data Appliance is a flexible, high-performance, secure platform for running diverse workloads on Hadoop and NoSQL systems. With Oracle Big Data SQL, Oracle Big Data Appliance extends Oracle’s industry-leading implementation of SQL to Hadoop and NoSQL systems. By combining the newest technologies from the Hadoop ecosystem and powerful Oracle SQL capabilities together on a single pre-configured platform, Oracle Big Data Appliance is uniquely able to support rapid development of new Big Data applications and tight integration with existing relational data.

    For more information on Oracle Big Data Appliance, visit Oracle.com

    Offer
    Learn more about Microsoft Azure Synapse Analytics
    Learn more about Oracle Big Data Appliance
    Sample Customers
    Toshiba, Carnival, LG Electronics, Jet.com, Adobe, 
    Caixa Bank
    Top Industries
    REVIEWERS
    Computer Software Company26%
    Comms Service Provider13%
    Manufacturing Company10%
    Healthcare Company10%
    VISITORS READING REVIEWS
    Computer Software Company21%
    Comms Service Provider12%
    Financial Services Firm9%
    Energy/Utilities Company6%
    VISITORS READING REVIEWS
    Computer Software Company25%
    Comms Service Provider14%
    Financial Services Firm14%
    Government6%
    Company Size
    REVIEWERS
    Small Business26%
    Midsize Enterprise22%
    Large Enterprise51%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise15%
    Large Enterprise68%
    REVIEWERS
    Small Business14%
    Midsize Enterprise14%
    Large Enterprise71%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise17%
    Large Enterprise65%
    Buyer's Guide
    Cloud Data Warehouse
    September 2022
    Find out what your peers are saying about Snowflake Computing, Microsoft, Micro Focus and others in Cloud Data Warehouse. Updated: September 2022.
    632,611 professionals have used our research since 2012.

    Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 48 reviews while Oracle Big Data Appliance is ranked 13th in Data Warehouse with 1 review. Microsoft Azure Synapse Analytics is rated 7.8, while Oracle Big Data Appliance is rated 8.0. The top reviewer of Microsoft Azure Synapse Analytics writes "Multifeatured, has better performance over other solutions, and lets users manage structured and unstructured information, but the platform needs to be more user-friendly". On the other hand, the top reviewer of Oracle Big Data Appliance writes "Provides clean, centralized data ". Microsoft Azure Synapse Analytics is most compared with Snowflake, Amazon Redshift, Azure Data Factory, SAP BW4HANA and Apache Hadoop, whereas Oracle Big Data Appliance is most compared with Oracle Exadata, Apache Hadoop, Teradata, IBM Integrated Analytics System and IBM Netezza Performance Server.

    We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.