TrustRadius: an HG Insights company

Oracle Data Masking and Subsetting vs. Untraceable

Save this comparison

Save this comparison

Oracle Data Masking and Subsetting

15 Reviews and Ratings

Untraceable

Add Product

Recommended Comparisons

    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Oracle Data Masking and Subsetting

    Score8 out of 10
    		N/AOracle Data Masking and Subsetting is designed to help database customers improve security, accelerate compliance, and reduce IT costs by sanitizing copies of production data for testing, development, and other activities and by discarding unnecessary data.N/A

    Untraceable

    		N/A
    Small Businesses (1-50 employees)
    		Untraceable (developed by Intraable AI Inc.) is an artificial intelligence (AI) workspace and Data Masking Software platform engineered for confidential and contractually restricted workflows. Designed for consultants, biostatisticians, and regulated-industry analysts operating across Health Economics and Outcomes Research (HEOR), pharmaceuticals, legal, and regulatory affairs, the software applies client-side semantic cloaking to text prior to model transmission. Architectural…

    $25

    per year per organization

    Pricing
    Oracle Data Masking and SubsettingUntraceable
    Editions & Modules
    No answers on this topic
    Pay as you go
    $25
    per year per organization
    Lite+
    $99
    per month per seat
    Offerings
    Pricing Offerings
    Oracle Data Masking and SubsettingUntraceable
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details——
    More Pricing Information
    Best Alternatives
    Oracle Data Masking and SubsettingUntraceable
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    No answers on this topic
    No answers on this topic
    Enterprises
    Perforce Delphix
    Score6 out of 10
    Perforce Delphix
    Score6 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Oracle Data Masking and SubsettingUntraceable
    Likelihood to Recommend
    9.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Oracle Data Masking and SubsettingUntraceable
    Likelihood to Recommend
    Oracle
    The tool is excellent when you need to provide all the details about your clients, yet hide their identity - all while maintaining the referential integrity of the data (so child-records of the masked parent record and maintain the same fake ID of the parent).
    Incentivized
    Ely Turkenitz
    IS Manager, Data Services
    Read full review
    Untraceable
    No answers on this topic
    Pros
    Oracle
    • It offers several ways in which you can mask your data; for example, you can choose to replace all names with "real fake names", or choose to replace all SSNs with existing SSNs, but randomly assigned. You control the algorithm.
    • It works on non-Oracle databases as well (in our case, we use it for both Oracle and SQL/Server).
    • The overhead is minimal (it doesn't take long to run, and it doesn't consume too many system resources.
    Incentivized
    Ely Turkenitz
    IS Manager, Data Services
    Read full review
    Untraceable
    No answers on this topic
    Cons
    Oracle
    • The learning curve was not trivial - but we got through it.
    • Cost - this product is not cheap.
    Incentivized
    Ely Turkenitz
    IS Manager, Data Services
    Read full review
    Untraceable
    No answers on this topic
    Alternatives Considered
    Oracle
    We also looked at Delphix: the tool was quite powerful, easy to use, and competitive from a cost standpoint. However, since our entire data warehouse environment is built on the Oracle technology stack, it made sense to us to use the Oracle product here, as it integrates very well with other Oracle database and ETL products.
    Incentivized
    Ely Turkenitz
    IS Manager, Data Services
    Read full review
    Untraceable
    No answers on this topic
    Return on Investment
    Oracle
    • We have many compliance regulations we need to adhere to. Without this tool, we were always taking a risk of exposing client information, and get penalized by the State of the Feds (the financial consequences are significant).
    • So while the tool doesn't save us money directly, it greatly reduces the risk we had been taking all these years. To some degree, this is much like an insurance policy.
    • Given the above, it also allows us to share information with other departments/agencies, in situations where before we simply couldn't take the risk of exposing client information.
    Incentivized
    Ely Turkenitz
    IS Manager, Data Services
    Read full review
    Untraceable
    No answers on this topic
    ScreenShots

    Untraceable Screenshots

    Screenshot of Screening every detected value before anything is sent. Each candidate is listed with its surrounding sentence so the user can confirm it in context, accept the proposed sequential cloak, or clear it as non-confidential. The counter tracks progress against the full set, here 81 of 81 value groups reviewed across sequential, semantic and name categories. Nothing is auto-cleared; the decision stays with the operator.Screenshot of A project folder holding original and cloaked documents side by side. Word, Excel and PowerPoint files are cloaked in place and versioned, so the cloaked copy that was sent to the AI remains available next to the original for audit. The confidentiality suite across the top covers cloaking, the Untraceable Protocol audit and certification view, and VaultScribe for AI drafting.Screenshot of What the user sees versus what the AI receives. The same cost-effectiveness table, shown twice: on the left the real values and the Ontario Case Costing Initiative source, on the right the version transmitted to the AI model, where every figure has been replaced with a semantic cloak such as SLC_0234 and the location with NAME_LOCATION_1. Structure, units, footnotes and the relationships between cells are preserved, which is why the model can still reason about the table.Screenshot of A VaultDelphi report. Several frontier models answer the same question blind, self-score their own evidence, and the panel runs further rounds until convergence or a documented failure to converge. Here the panel did not reach consensus on an incidence figure, and the report says so, naming the methodological split and the sources behind each position rather than returning a single confident number.