Survey: Cloud is Platform of Choice for Analytics Databases

Cloud adoption and cloud migrations remain strong among enterprises, particularly for operational and analytic databases. That’s the findings of a recent 451 Research survey, which also found data lake adoption is also growing, and there is significant interest in data lakehouse environments, which combine a data warehouse’s data structure and management features with the low-cost storage used for a data lake.

The “Voice of the Enterprise: Data & Analytics, Data Platforms 2022” survey of 482 IT decision-makers found that enterprise appetite for all things cloud shows no signs of letting up. 451 Research, which is part of S&P Global Market Intelligence, noted some of the major trends in this market bolstered by the survey results.

Which type of cloud is preferred?

The survey found that private cloud is the most favored environment for deploying data platforms. Forty-six percent of survey respondents use an on-premises private cloud, in addition to 27% using a managed database as a service, or DBaaS, offering. Meanwhile, 66% of respondents cite public cloud as a deployment location for their data platform systems.

Multicloud and hybrid cloud are frequently used. Forty percent of organizations report using multicloud deployments, while 41% report using hybrid cloud.

See also: Cloud Data Platforms: Data Shifts to the Cloud 

Where do different workloads reside?

Despite the enthusiasm for cloud, the survey found that there is no rush to migrate existing on-premises operational workloads to cloud. Given a choice of plans for existing on-premises relational operational workloads, 59% of respondents choose to remain on-premises.

It is a different story for new operational workloads, relational databases dominate, and the cloud is the preferred location. Fifty-seven percent of organizations prefer cloud environments over on-premises environments for new operational workloads.

Increasingly, as companies more fully embrace analytics, many companies have complemented their operational databases with analytic databases. An analytic database is a read-only system that stores data on business metrics such as sales performance and inventory levels. Business analysts, corporate executives, and other workers run queries and reports against an analytic database.

According to the survey, existing on-premises analytic databases are seeing increased pressure from data lakes. Thirty-eight percent of organizations are sticking with the same supplier for their analytic databases. Of that total, about one-third (13% of respondents) prefer the same analytical database deployed in the cloud, while close to two-thirds (25%) are keeping the same supplier on-premises. Data lakes, on the other hand, are preferred over analytic databases by 28% of respondents. However, cloud is the choice for new analytic workloads. Fifty-six percent of respondents prefer cloud environments over on-premises environments for new analytical workloads.

Role of data lakes

Data lake adoption remains strong because data lakes provide agility and workload flexibility. Specifically, data lakes offer a centralized repository designed to store, process, and secure large amounts of structured, semi-structured, and unstructured data. It can store data in its native format and process any variety of it, ignoring size limits.

Forty-five percent of enterprises with a data lake in deployment or planned cite improved business agility as the primary expected benefit of a data lake. For organizations that have existing data lake applications or plan to within a year, top use cases include analytics such as business intelligence (66% of respondents), operational applications (56%), data science (53%), and migration/staging (45%).

As noted, there is growing interest in data lakehouses. The main advantage of a data lakehouse is that it can simplify the overall data engineering architecture by providing a single staging tier for all data and all types of applications and use cases. Seventy percent of enterprises are currently using a data lakehouse, piloting one, or planning to implement one within the next 12 months. That figure rises to 93% among enterprises that already have a data lake in production.

Many data lakehouse offerings are available as cloud-only. Interestingly, there is an untapped market for solutions offered in cloud and on-premises. Of the 34% of all respondents not using cloud-only databases today, 38% say their organization would be more likely to use cloud-only databases if they were also available on-premises. Sixty-four percent of those using cloud-only databases say their organization would use those databases for more initiatives if they were also available on-premises.

Final word: Putting cloud databases into perspective

There are many use cases for cloud database platforms, including data warehousing, transaction processing, data science exploration or deep learning, stream and event processing, and operational intelligence. Through the integration and layering of solutions, organizations can integrate in-house or third-party analytics, visualization, and other tools.

With more organizations than ever before deciding to move assets to cloud-based data platforms, they expect to realize advantages and opportunities that come from transitioning from legacy, on-premises technology to an on-demand environment. 

The business case for migrating databases to cloud is compelling. Enterprises are embracing the transition. Gartner estimates that in 2022 over 50% of all database revenue will come from cloud platforms. That is up from about 30% in 2018 and is expected to rise to 70% by 2025. 

As long-term digital transformation and modernization initiatives continue, enterprises will shift to the cloud. That said, planning is the key to a successful cloud migration for any application, service, and especially databases.

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