Apache Hadoop and Kovair Data Lake are competing products in the big data management space. Apache Hadoop seems to have an edge in handling large-scale applications with strong community support and flexibility, while Kovair Data Lake's integrated approach and user-friendly interface are advantageous for enterprises focusing on long-term data strategies.
Features: Apache Hadoop offers distributed processing and storage capability, modular architecture for customizability, and scalability for large data volumes. Kovair Data Lake stands out with strong integration capabilities, user-friendly interfaces, and effective data pipeline management.
Ease of Deployment and Customer Service: Apache Hadoop's deployment is complex, requiring substantial configuration and skilled resources, with community forums as primary support. Kovair Data Lake provides streamlined deployment with professional customer service, ensuring quicker setup and resolution.
Pricing and ROI: Apache Hadoop requires lower initial investment due to its open-source nature, offering high ROI if managed well. Kovair Data Lake involves higher upfront costs due to enhanced features, providing better ROI for businesses needing efficiency and integration.
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.
- 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/
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.