Data Management in Cloud Environments
Data cloud storage enables the storage of files and data in an off-site location and can be accessed using a private network or public internet services. The service provider is responsible for hosting, security, maintenance, and managing this data. Data management in cloud environments is crucial for ensuring the security, accessibility, and efficiency of data storage and processing. With the increasing reliance on cloud infrastructure for business operations, it is essential to have robust data management strategies in place to ensure the integrity and availability of data and meet compliance requirements. It involves various activities such as data backup, recovery, security, and governance, which can be complex and time-consuming in a traditional on-premises data center. However, cloud-based data management solutions offer a range of benefits, including improved scalability, flexibility, and cost-effectiveness, making them a popular choice for organizations looking to optimize their data management processes.
Adoption of Cloud Services
The evolution of Storage as a Service is an essential component of cloud computing with support for ACID properties and the provision of different data models and database options. This article undertakes a review of cloud computing for data management and storage.
Cloud computing has become a central component of running a business for less than a decade. The main advantage of cloud computing is its economies of scale and flexibility. Cloud computing can best be understood as the on-demand delivery of IT and computing services such as Software, databases, networking, servers, analytics, and intelligence over the internet with a pay-as-you-go pricing model. It is an alternative to buying servers and services on a need-basis instead of traditional means such as physical servers and data centers. As the world has increasingly moved towards remote work, cloud-based services are adopted widely as a new technology standard. The companies that provide such services have been widely able to identify and address their concerns, such as security and privacy, paving the way for a smoother transition.
Understanding Cloud Computing Models and Terminology
The types of cloud computing models adopted depend on several factors but majorly, the utility of these services and the size of the company in question. The four widely identified types are:
- Public cloud
- Private cloud
- Hybrid cloud and
- Multiclouds
Public clouds typically create IT infrastructure with options for provision on and off clients’ premises. Private clouds are dedicated to end-users and groups behind a firewall with remote access, and they are usually off-premises on rented data centers. There are a few subtypes under these, such as dedicated and managed private clouds depending on their services. Hybrid clouds consist of IT environments from multiple environments using LANs, WANs, APIs, and VPNs. These can include one or many private and public clouds. Multiclouds, on the other hand, consist of using more than one private or public cloud from more than one vendor.
Each cloud provider has a set of services, such as Platform as a Service, Infrastructure as a Service, and Software as a Service, among others. Another such component is Storage as a Service. Storage as a service includes both data management and data storage. Cloud data storage is mainly about the efficient choice of storage on a cloud, while data management is about data integrity, access, growth, and maintenance, including the aspects of data security.
Key players in Data Management and Storage
When it comes to cloud computing, here are a few market players that have gained more popularity as compared to others, and they are as below:
- Amazon Web Services (AWS)
- Microsoft Azure
- Google Cloud Platform (GCP)
- Alibaba Cloud
- Oracle Cloud
- IBM Cloud
- Tencent Cloud and many others
Cloud storage, however, is a minor aspect of cloud computing and data management, and the key market players in the cloud storage space are as follows:
- Microsoft OneDrive
- iDrove
- Google Drive
- Dropbox
- Zoolz Cloud Backup and many others.
The difference is primarily attributed to the large-scale personal and small enterprise use of these platforms compared to the adoption of big cloud providers, such as Amazon AWS and Microsoft Azure, that companies prefer for more wide-scale adoption of cloud platforms or services.
In contrast to the list above, the key players in the data management niche are as below:
- VMware
- Flexera Rightscale
- IBM Cloud Orchestrator
- BMC Cloud Lifecycle Management
- Apache CloudStack
- Scalr and many others
Selection criteria for data storage options
Data storage in the cloud can be understood by looking at the choices provided by notable industry names that provide multiple options for storage. Three cloud providers are analyzed for their storage options as below:
- Amazon AWS
- Microsoft Azure
- Google Cloud Platform
Amazon AWS
As of date, there are mainly seven different types of storage services by Amazon AWS as below:
- Simple Storage Service (S3): S3 is the most widely used object storage service provided by AWS. It has options for storing mobile and web applications, archives, backups, and analytics. S3 has flexible, economical, dynamic pricing options and accessible everywhere service.
- Elastic Block Storage (EBS): EBS is a faster storage option with low latency and high speed for input/output operations per second. It has more agility for scalability and provides consistent and predictable performance.
- Elastic File System (EFS): Like EBS, EFS is also speedier than S3. It is used more in cases where large data sizes are involved. EFS also allows EC2 instances to be accessed concurrently, allowing efficient data retrieval compared to EBS.
The other relatively less used services in AWS include:
- Amazon FSx for Lustre
- Amazon FSx for Windows File Server
- Amazon S3 Glacier
- AWS Storage Gateway
These services focus overall on the difference in the features of data storage, capacity, scalability, availability, security, and access control. Pricing additionally plays an essential factor when choosing one of these services.
Microsoft Azure
Azure has a similar option for data storage services. The essential data services in Azure are as below:
- Azure Blobs: Used for large-scale storage in both binary and text format data. It is mainly used as a service in support of Big Data analytics as part of data pipelines and data lakes.
- Azure Files:It is a file server service with support for SMB and NFS files used in operating systems such as Linux and Windows. It is mainly in use for admin purposes using Windows Server machines. It also has a suitable access control mechanism with additional scripting and tooling interface.
- Azure Queues:This is a messaging service provider between different application components. Authenticated calls are provided for additional security in communication with a queue for asynchronous communication.
- Azure Disks:Disks are storage volumes at the block level for use in services such as Azure Virtual Machines. It has several security features and access control mechanisms that can define snapshots and disk roles. It provides for high availability zones with backup support and support for encryption.
- Azure Tables:This is a NoSQL-based service with no schema for the tables or non-relational databases.
The emphasis on storage features, as specified by Microsoft, includes that high availability, security, scalability, management, and accessibility.
Google Cloud Platform
The critical services provided by Google Cloud Platform include:
- Cloud Firestore
- Cloud Bigtable
- Cloud Storage
- Cloud SQL
- Cloud Spanner
- BigQuery
- Memorystore
The selection of these services is categorized on the requirement below:
- The type of database, such as unstructured or structured
- Analytical or transactional model for the database
- Provisioned services or autonomous
- Local or regional against the global requirement of data storage
- Type of scaling required as vertical or horizontal
The overall emphasis of all the platforms discussed is on the features such as transaction types, storage types, capacity, speed, durability, accessibility, management, and security.
Data Management in the Cloud: Challenges and Benefits
Cloud data management, unlike data storage, is more closely associated with cloud service administrative and management roles. It supports data management platforms, policies, and procedures for organizations that provide better business control. The key factors in data management in cloud services can be summarized below:
- Privacy and security: Perhaps the central component of any cloud services provider, privacy and security have outgrown other factors from being a cause of concern to a selling point for cloud management platforms. According to some estimates, the security and access control options available with providers are better than even on-premise options.
- Data integration:Data integration can be about streamlining different data types and the passage of data between different services. Synchronization of data and services plays a vital role while using cloud services. It is a significant factor, especially in setting data pipelines using ETL (Extract transform load) batches for analytical purposes. Migration of data from on-premise to the cloud can also help uncover inefficiencies in data management.
- Data and metadata management:Centralized control of services using data is essential for businesses. With the increase in cloud management platforms available, support for intelligent services and visualization tools is in demand. Machine learning-based usage of metadata allows more efficient data governance and curation.
- Support for auxiliary services:Auxiliary services are unconventional services specific to a niche or segment of the industry. An example is the use of AI and machine learning models in analytics and data science services.
- Data governance and quality:Data injection is the responsibility of the client; however, data control and quality management aim for efficient storage for ease of business.
Summary
The benefits of a sound data management system on cloud platforms compared to on-premise can include flexible pricing options, far better scalability options, anywhere access promoting low latency, less management and maintenance options, security assurance, backup mechanisms, and centralized management options. Each option plays a vital role in decision-making for a data management platform. On the contrary, challenges can include confusing pricing options, egress fees levied on departing services, integrity concerns, and security risks for access control, among others.
