Compare Kovair Data Lake vs. Microsoft Parallel Data Warehouse

Kovair Data Lake is ranked 29th in Data Warehouse while Microsoft Parallel Data Warehouse is ranked 14th in Data Warehouse with 2 reviews. Kovair Data Lake is rated 0, while Microsoft Parallel Data Warehouse is rated 4.6. On the other hand, the top reviewer of Microsoft Parallel Data Warehouse writes "Concurrency issues forced the customer to use the raw DB as a secondary solution". Kovair Data Lake is most compared with , whereas Microsoft Parallel Data Warehouse is most compared with Oracle Exadata, Snowflake and Teradata.
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Ranking
29th
out of 30 in Data Warehouse
Views
29
Comparisons
12
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
14th
out of 30 in Data Warehouse
Views
2,964
Comparisons
2,201
Reviews
2
Average Words per Review
116
Avg. Rating
4.5
Top Comparisons
Also Known As
Microsoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data Warehouse
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Kovair
Microsoft
Overview

Kovair Data Lake is a central database that comes with SQL server support. This makes it capable of storing data from multiple projects residing in diversified tools used by an organization. Based on organizational needs, the stored data is then segregated by departments or business units. Kovair Data Lake also comes with a very intuitive UI interface for managing and monitoring of the Data Lake.

Many organizations use enterprise data warehouses to meet both operational and reporting needs. However, apart from offering a storage and management facilities, there are certain limitations that organizations continue to face. These are –

- Real-time synchronization of data within a centralized data storage

- Traceability and governance of stored data

- Low-cost storage infrastructure compared to Big Data or Data Warehouse

- Handling of low volume but highly diversified data

- Prescriptive analytics that will aid in taking data-driven decisions and on-time service delivery

    Kovair has been a market leader in the domain of data integration with a marquee of clients from networking, semiconductor, telecom, manufacturing, banking and finance. Over the recent years, it has witnessed a shift in focus for organizations using multiple tools and different teams. While Kovair Omnibus provides the support for features like traceability, cross tool reporting, and task-based workflow that is simply not enough! Customers today are looking for central data store where data coming from different tools used in an organization could be accumulated in its native format.

    Data Lake presents a low-cost alternative to exploding storage and processing costs of traditional warehouses.

    While traditional data warehouses store data in hierarchical format. Data Lake offers a central database repository with a flat architecture for storing the data. This protects the data from unwanted manipulation, enabling businesses to take informed decisions accurately and building a better business-customer relationship.

    Product Highlights:

    - Large Data Repository for Central Administration

    - Tool Extractors with WS/SQL Communication Support

    - Web-based Data Lake Portal

      More details - https://www.kovair.com/data-lake/

      The traditional structured relational data warehouse was never designed to handle the volume of exponential data growth, the variety of semi-structured and unstructured data types, or the velocity of real time data processing. Microsoft's SQL Server data warehouse solution integrates your traditional data warehouse with non-relational data and it can handle data of all sizes and types, with real-time performance.

      Offer
      Learn more about Kovair Data Lake
      Learn more about Microsoft Parallel Data Warehouse
      Sample Customers
      HSBC, NVIDIA, APPLIED MATERIALS, Allscripts, CISCO, HoneywellAuckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel Europe
      Find out what your peers are saying about Oracle, Teradata, Micro Focus and others in Data Warehouse. Updated: October 2019.
      372,185 professionals have used our research since 2012.
      We monitor all 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.
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