Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Amazon Redshift is a fully administered, petabyte-scale cloud-based data warehouse service. Users are able to begin with a minimal amount of gigabytes of data and can easily scale up to a petabyte or more as needed. This will enable them to utilize their own data to develop new intuitions on how to improve business processes and client relations.
Initially, users start to develop a data warehouse by initiating what is called an Amazon Redshift cluster or a set of nodes. Once the cluster has been provisioned, users can seamlessly upload data sets, and then begin to perform data analysis queries. Amazon Redshift delivers super-fast query performance, regardless of size, utilizing the exact SQL-based tools and BI applications that most users are already working with today.
The Amazon Redshift service performs all of the work of setting up, operating, and scaling a data warehouse. These tasks include provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine.
Amazon Redshift Functionalities
Amazon Redshift has many valuable key functionalities. Some of its most useful functionalities include:
Reviews from Real Users
“Redshift's versioning and data security are the two most critical features. When migrating into the cloud, it's vital to secure the data. The encryption and security are there.” - Kundan A., Senior Consultant at Dynamic Elements AS
“With the cloud version whenever you want to deploy, you can scale up, and down, and it has a data warehousing capability. Redshift has many features. They have enriched and elaborate documentation that is helpful.”- Aishwarya K., Solution Architect at Capgemini
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/
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