ENEA Polyhedra vs Google BigTable comparison

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59 views|39 comparisons
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78 views|35 comparisons
100% willing to recommend
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Eric Smets
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    Ranking
    15th
    Views
    59
    Comparisons
    39
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    14th
    Views
    78
    Comparisons
    35
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Comparisons
    Also Known As
    Polyhedra
    BigTable
    Learn More
    Overview
    Polyhedra is a family of compact, lightweight, SQL relational database management systems (RDBMS) optimized for embedded systems applications. Built on an ironclad clientserver architecture, Polyhedra in-memory database system (IMDB) and Polyhedra FlashLite provide a secure data repository for embedded systems, mobile devices and server-based applications demanding the utmost in performance and reliability.
    Cloud Bigtable is Google's NoSQL Big Data database service. Bigtable is designed to handle massive workloads at consistent low latency and high throughput, so it's a great choice for both operational and analytical applications, including IoT, user analytics, and financial data analysis.
    Sample Customers
    Xilinx, Freescale Semiconductor, AMD
    Absolutdata, Aerospike, Affini-Tech, Akselos, Alacris Theranostics, Allthecooks, AloTech, APMEX Inc., Applibot, Appogee, BeDataDriven, Bitmovin, CloudBerry

    ENEA Polyhedra is ranked 15th in Non-Relational Databases while Google BigTable is ranked 14th in Non-Relational Databases. ENEA Polyhedra is rated 0.0, while Google BigTable is rated 8.6. On the other hand, the top reviewer of Google BigTable writes "Extremely scalable, quite stable and easy to deploy". ENEA Polyhedra is most compared with , whereas Google BigTable is most compared with .

    See our list of best Non-Relational Databases vendors.

    We monitor all Non-Relational Databases 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.