AtScale Adaptive Analytics (A3) vs Netezza Analytics comparison

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239 views|204 comparisons
0% willing to recommend
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235 views|103 comparisons
76% willing to recommend
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Pros
"The GUI interface is nice and easy to use."

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"The performance of the solution is its most valuable feature. The solution is easy to administer as well. It's very user-friendly. On the technical side, the architecture is simple to understand and you don't need too many administrators to handle the solution.""Speed contributes to large capacity.""For me, as an end-user, everything that I do on the solution is simple, clear, and understandable.""Data compression. It was relatively impressive. I think at some point we were getting 4:1 compression if not more.""The need for administration involvement is quite limited on the solution.""It is a back end for our SSIS, MicroStrategy,, Tableau. All of these are connecting to get the data. To do so we are also using our analytics which is built on the data.""The most valuable feature is the performance."

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Cons
"There was an issue with the incremental aggregation not working as indicated.""The product was not able to meet our 10 second refresh requirements.""The organization of the icons is not saved across users."

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"This product is being discontinued from IBM, and I would like to have some kind of upgrade available.""The most valuable features of this solution are robustness and support.""I'm not sure of IBM's roadmap currently, as the solution is coming up on its end of life.""Disaster recovery support. Because it was an appliance, and if you wanted to support disaster recovery, you needed to buy two.""Administration of this product is too tough. It's very complex because of the tools which it's missing.""The Analytics feature should be simplified.""The hardware has a risk of failure. They need to improve this.""The solution could implement more reporting tools and networking utilities."

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Pricing and Cost Advice
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  • "Expensive to maintain compared to other solutions."
  • "For me, mainly, it reduces my costs. It's not only the appliance cost. There are also support costs and a maintenance costs. It does reduce the costs very drastically."
  • "The annual licensing fees are twenty-two percent of the product cost."
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    Top Answer:Here are some things to consider when migrating from Netezza to AWS Redshift A. Migrating your data from Netezza to Redshift may be done using methods such as: o Use a third-party tool to export… more »
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    11th
    out of 22 in Hadoop
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    235
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    103
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    Also Known As
    AtScale, AtScale Intelligence Platform
    Learn More
    Overview

    AtScale is the leading provider of intelligent data virtualization for big data analytical workloads, empowering citizen data scientists to accelerate and scale their business’ data analytics and science capabilities and ultimately build insight-driven 

    AtScale connects people to live disparate data without the need to move or extract it, leveraging existing investments in big data platforms, applications and tools. AtScale creates automated data engineering using a single set of semantics so consumers can query live data (either on premise or in the cloud) in seconds without having to understand how or where it is stored—providing security, governance and predictability in data usage and storage costs.

    Benefits:

    No data movement: AtScale is agnostic to data platforms and data location, whether on-premises or in the cloud, in a data lake or a data warehouse.

    Automatic “smart” aggregate creation: AtSacle’s intelligent aggregates adapt to the data model and how it is used, automating the data engineering tasks required to support those activities and reducing time spent from weeks to hours.

    Use your existing BI and AI tools: AtScale provides access to live, atomic-level data without the user needing to understand where or how to access the data, so you can keep using your tools of choice.

    No more extracts or shadow IT: AtScale eliminates the need for extracts with a single, consistent, governed view of live data, regardless of which BI and AI tools are used.

    Data-as-a-service: AtScale allows metadata to be created once, with centrally defined business rules and calculations, exposing data assets as a service.

    Data platform portability: Models built in AtScale are portable, with no need to recreate them for different platforms. AtScale can easily be repointed to new data platforms, making migration seamless to business users.

    Faster time-to-insight: AtScale reduces time-to-insight from weeks and months to minutes and hours. AtScale virtual models can be created and deployed in no time, with no ETL or data engineering.

    Future-proof your data architecture: AtScale alleviates the complexities of data platform and analytics tool integration, making cloud, hybrid-cloud and multi-cloud data architectures a reality without compromising performance, security, agility or existing governance and security policies.

    Features:

    Design CanvasTM: AtScale’s Design Canvas visually and intuitively connects to any data platform, allowing you to create virtual multidimensional cubes without ETL.

    Autonomous Data Engineering: Just-in-time query optimization that anticipates the needs of the data consumer.

    Universal Semantic LayerTM: A workspace with a Design Canvas for your data consumers to define business meaning and get a single-source-of-truth.

    Security & Data Governance: Centralized security policy to decentralize access using the tenants of Zero Trust.

    Virtual Cube Catalog: A gateway to data that is easily discoverable and frictionless—and available to use every day, en masse.

    AtScale connects people to live disparate data without the need to move or extract it, leveraging existing investments in big data platforms, applications and tools. AtScale creates automated data engineering using a single set of semantics so consumers can query live data (either on premise or in the cloud) in seconds without having to understand how or where it is stored—providing security, governance and predictability in data usage and storage costs.



    IBM Netezza Analytics is an embedded, purpose-built, advanced analytics platform that empowers analytic enterprises to meet and exceed their business demands. As features, it can predict with more accuracy, deliver predictions faster and respond rapidly to changes.
    Sample Customers
    Rakuten, TD Bank, Aetna, Glaxo-Smith Kline, Biogen, Toyota, Tyson
    A leading online advertising network
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm27%
    Manufacturing Company11%
    Computer Software Company7%
    Healthcare Company6%
    No Data Available
    Company Size
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise8%
    Large Enterprise75%
    REVIEWERS
    Small Business25%
    Midsize Enterprise17%
    Large Enterprise58%

    AtScale Adaptive Analytics (A3) is ranked 5th in Data Virtualization while Netezza Analytics is ranked 11th in Hadoop. AtScale Adaptive Analytics (A3) is rated 5.0, while Netezza Analytics is rated 7.4. The top reviewer of AtScale Adaptive Analytics (A3) writes "The GUI interface is nice and easy to use, but the organization of the icons is not saved across users". On the other hand, the top reviewer of Netezza Analytics writes "ARULES() function is the fastest implementation of the associations algorithm (a priori or tree) I have worked with". AtScale Adaptive Analytics (A3) is most compared with Denodo, Dremio, ThoughtSpot, SAP BusinessObjects Business Intelligence Platform and Alation Data Catalog, whereas Netezza Analytics is most compared with Spark SQL and HPE Ezmeral Data Fabric.

    We monitor all Data Virtualization 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.