The most suitable place for most businesses to store their Big Data is within the cloud. Utilising cloud services for data storage and increasingly for analytics means businesses are outsourcing time and effort associated with storing and managing large sets of data. The implications of power consumption, space, infrastructure and security become the responsibility of your cloud service provider, and usually, they are well equipped and prepared to deal with these factors.
An additional benefit of using cloud solutions is the ability to scale. Most plans enable businesses to start off fairly small and then expand the capacity available for storing data as demand continues to increase. Some larger providers offer additional services to manage AI, analytics and other tools without having to shift your data away from the cloud.
analytics, and data visualization needs without your valuable data ever leaving the safety of the cloud.
Amazon Web Services S3
Amazon introduced its first platform-as-service offering in 2006 and created a model for nearly all other cloud storage and computer services provided. The Amazon data lake service referred to as the Amazon Simple Storage Service (S3) and is utilised by millions of customers worldwide. AWS continues to be the leading cloud storage solution for big data services in terms of popularity. AWS generated nearly $10 billion in revenue for Amazon in the last quarter of 2019.
Microsoft Azure Data Lake
A rival competitor to AWS, Microsoft launched its service in 2010 and quickly established a range of tools to enable businesses that operate with large data sets and allow operations to be performed in the cloud. Microsoft has years of experience in managing some of the biggest processing and analytics operations worldwide. Azure’s services include Azure Data Lake which is targeted at managing the businesses with complex data requirements.
Google Cloud Storage
Google’s cloud platform is developed on the same technology that drives its own big-data services such as Youtube and Google Search. It offers a range of storage and data-lake focused services, capable of scaling and managing excessively large amounts of data. Google provides a range of pricing plans applied to different datasets and customers have the ability to choose their storage location. Furthermore, Google’s data storage solutions have generated zero net carbon emissions since 2007.
Oracle’s established database platform is available via the Oracle Cloud service providing a flexible and scalable storage option. The service is regarded for its good security features and real-time encryption of data on the platform. The system uses its own advanced machine learning processes to automate many of the data procedures, reducing potential errors related to manual data entry.
IBM provides a range of data lake solutions depending on business requirements. Like most other solutions, IBM offers the option to scale up as you expand and store large volumes of data. IBM provides ‘cognitive’ analytical tools via the Watson AI platform that can be added with the stored data on IBM cloud services.
While Alibaba may not rival the major leaders in western nations, Alibaba is developing a strong presence. Being the biggest big data cloud service provider in China, the business has a significant customer base across Asia and offers similar analytics, security and AI tool to rival other US-based platforms. Alibaba provides a choice of pay-as-you-go and monthly subscription services. Recent industry reviews suggest the services provided may not meet the offerings in the US and Europe but pricing is viewed as very competitive.