Organizations need a data warehouse to perform data analytics and get relevant information for business, but should you build it in the cloud or on-premises?
The cloud data warehouse market is expected to reach $39.1 billion by 2026 due to the growing adoption of IoT technologies and the use of cloud data to process data from various tools. Still, the comparison depends on important factors such as scalability, cost, deployment, economies of scale, application, reliability, and security.
On-Premises Data Warehouse: What Is It?
On-premises software and hardware require significant upfront investment in software and hardware licenses, as well as dedicated staff and LAN access for management and operation.
What Is Cloud-Based Data Warehouse?
Cloud data warehouse is a service that helps companies collect, store, organize, and manage the data they use for a variety of purposes, such as monitoring, analysis, and consulting.
Cloud Vs. On-premise Data Warehouse
In today’s business environment, cloud solutions are outperforming on-premises warehouse. The main reason for this choice is the shared computing resources that provide flexibility for organizations of all shapes and sizes.
However, many loyal users continue to use on-premises storage for a variety of reasons, including lower optimization costs, compliance, and data security. With both options being used for different use cases, how do you choose the best approach for your organization? Here are the key points to consider.
Scalability
On-premises data warehouses need to scale. Every time you want to increase processing power or storage capacity, you have to buy additional storage, and setting up and handling more data requires a lot of time and work. In addition, if you need to reduce capacity for any reason, you may be left with unwanted hard drives.
With cloud storage, you can increase or decrease your subscription depending on your needs. You don’t have to worry about infrastructure: you can ask your cloud provider to provide the scalability and storage you need. So, if scalability is an issue, a cloud solution is a great option.
Deployment
The most obvious difference between on-premises and cloud storage is how they are deployed. On-premises storage is when software is only installed on a company’s systems and servers.
Cloud-based applications, on the other hand, can be hosted on a public or private cloud. With a public cloud, companies provide their data and resources to an external data warehouse service provider and access to other public networks. When choosing a private cloud, access to data is restricted, and resources are allocated according to the company’s needs.
Administrative Oversight
Your IT department is fully responsible for the IT systems in your on-premises environment. With cloud warehouse, you share this responsibility with the vendor and, especially in a fully managed DWaaS environment, relinquish some control over the management of the storage platform.
While some IT departments see this as a risk, most rather see it as a combination of opportunity and risk. The fact that all major cloud warehouse vendors offer service-level agreements that guarantee a minimum level of availability should allay concerns about losing control of the system.
Economies of Scale
Cloud data warehouse eliminates the need to purchase or configure physical servers; instead, the service provider handles the hardware, upgrades, and management. You pay for the processing time and storage space you use. Service providers use a pay-as-you-go pricing model, allowing customers to pay only for services they use or can afford. On-premises storage is more expensive than cloud storage because it requires staff, equipment, and expertise.
Workload Adaptability
Unless you scale your environment, on-premises data warehouses are often limited by physical infrastructure and initially deployed capacity. Upgrades and changes can be complex and time-consuming, unlike the flexibility of cloud storage, which can quickly adjust compute and storage resources to meet changing business needs.
Security
In general, cloud data warehouse is more secure than on-premises data warehouse from a usage perspective. Contrary to popular belief, cloud solutions move data to another platform, whereas on-premises DWS stores all data on an organization’s network. As a result, data leaves the workplace. For example, relevant stakeholders often need to access and transfer data to external partners such as the legal department, accountants, and auditors.
Cloud solutions prioritize security, especially for data-centric operations. For example, Google BigQuery is an integrated server less data warehouse that allows employees to access data remotely through a secure and reliable connection.
Application
For on-premise data stores, the system specification can be customized to meet specific performance requirements such as memory size, processor power, etc. Performance often depends on the physical location of the data and processing resources, which may need to be improved. Although the performance and scalability of on-premises systems may be limited, such data warehouses have low network latency because the data processing is performed on the internal network.
Cloud data warehouses, on the other hand, utilize a distributed processing architecture that processes data in parallel on distributed clusters. The distributed architecture provides consistent performance with increasing parallelism. However, since cloud data warehouses depend on network connectivity between the corporate center and the cloud service provider’s data center, they can sometimes experience network latency.
Overview
There are both on-premises and cloud data warehouse options, so you can choose the one that best suits your needs. However, you don’t necessarily have to choose one or the other. A hybrid strategy that combines both data warehouse is a popular way to build a robust data management system. With this strategy, you can combine cloud storage with dedicated on-premise data warehouse for sensitive data and enjoy the benefits of low network latency as well as server scalability and performance.
