Real estate service providers handle large volumes of diverse data, use multiple property metrics, and generate complex analytics reports. While these tasks can be done on-premise, the industry is shifting towards the cloud.
Decision-makers are migrating their applications or choosing the cloud from the start, as maintaining a local data center has become too costly in resources and effort compared to the out-of-the-box tools offered by cloud providers.
From luxury residential projects such as Saadiyat Shores to commercial real estate platforms and property marketplaces, modern solutions require scalable infrastructure capable of processing real-time market data, customer analytics, and high-resolution property media across multiple regions.
This article will explore why the cloud is the best choice for real estate solutions and discuss its limitations.
Why the cloud is the best option for real estate
Cloud providers own and operate a network of data centers across different regions, which offers two major benefits: flexibility and freedom from infrastructure maintenance. The list of advantages for real estate companies is even more extensive.
Avoid costly hardware purchases
Proptech startups, often with limited budgets and a need to launch quickly, can’t risk investing in expensive on-premise hardware for a Proof of Concept (PoC) or Minimum Viable Product (MVP). Setting up on-premise infrastructure is also difficult and time-consuming.
However, processing large data volumes from mortgage providers and clients requires significant computational power. Cloud computing provides this power without the need to spend thousands on a local data center, and the infrastructure is available immediately, speeding up time to market.
Pay only for what you use
Real estate businesses rely on calculations for tasks like investment analysis, which require substantial but infrequent computational resources. An on-premise data center would often sit idle, wasting money. The cloud’s pay-as-you-go model means you only pay for the computational power you use.
You can also save money by running calculations overnight during off-peak hours. Cloud providers also offer serverless tools, like AWS Lambda, that manage server load automatically, preventing the long delays that could happen with a heavily loaded on-premise server.
Architectural flaws are less critical
Initial software architecture may not anticipate future needs, such as a vacation rental platform expanding nationwide. An on-premise data center not designed for scalability would eventually face costly performance issues, requiring either more powerful servers or a complete architectural overhaul.
Cloud computing is more forgiving of such flaws. Services like Lambda can alleviate server load, allowing applications to scale easily without impacting the user experience.
Downtime risk approaches zero
Real estate agents need constant system access. An on-premise data center is vulnerable to fires, natural disasters, or other emergencies that could cut off access to infrastructure and data. Cloud providers’ data centers are distributed geographically. If one center goes down, traffic is automatically redirected to a healthy server in another region, often with no noticeable disruption.
DevOps expertise is less critical
Configuring on-premise infrastructure is complex and requires a highly skilled DevOps team to manage performance and security. The cloud simplifies this by offering services that automate DevOps tasks. For example, creating a backup can be done in a few clicks, whereas on-premise it is a manual process prone to human error.
Real estate analytics in the cloud
The cloud’s on-demand computational power is ideal for real estate data analytics. Consider a consulting client we assisted who needed to add analytics to their solution. They extract data from about 400 Multiple Listing Services (MLSs), which involves processing a massive volume of information. The cloud provides several benefits in this scenario.
Better data quality control
Real estate agents can make data entry errors, like entering an incorrect address, which affects analytics accuracy. Cloud service providers offer tools for automated data correctness and consistency checks, helping maintain high data quality with minimal loss.
The flexibility we love
With on-premise infrastructure, integrating other data sources is a major challenge requiring custom connectors. This isn’t feasible when dealing with hundreds of sources. Cloud platforms are more flexible, offering built-in connectors that allow you to quickly connect with open-source systems like Google Maps or Zoho and start extracting data immediately.