This article was originally published on the Red Hat Blog. Click HERE to read the original article in its entirety.
Databases have been traditionally viewed as the definition of a monolith — never intended to be broken down into microservices and containerized. A lot has changed in a short period of time and while containerizing a database may not be as straightforward as containerizing an application, the benefits greatly outweigh the challenges. Databases need the agility, portability and scalability that containerization can offer and organizations are moving to take advantage of these benefits.
A recent Red Hat-sponsored study conducted by Gartner Peer Insights surveyed 200 tech leaders across the globe to find out how organizations are adopting databases on containers and Kubernetes, what technologies they are considering for deploying these workloads and more.
The full report is available here, and we’ve highlighted some of the key findings below.
Adoption is increasing — and for a variety of use cases
The vast majority of respondents are well on their way to operationalizing databases on containers, with 69% stating that they are in the middle or advanced stages of adoption. Of that 69%, 4% believe they are far along in the process and 65% believe they are somewhere in the middle — having started adoption, but not using databases on containers in a full-fledged manner as of yet.
Additionally, given the number of tools now available to help ease adoption, we expect these numbers to continue to grow. Kubernetes Operators and Helm charts help automate day-1 and day-2 operations like installation, configuration and updates and upgrades, as well as help with lifecycle management of applications, greatly simplifying adoption and ongoing maintenance for organizations.
The reason for adoption varies, with operational or transactional use cases being the number one reason, as reported by two-thirds (67%) of the respondents. Nearly even with operational use cases, 65% of respondents are using databases on containers and Kubernetes to help with data analytics and AI/ML. A significant number of respondents (37%) are using containers to modernize their traditional databases that are deployed on virtual machines or bare metal servers.
Mixed methods for deploying
When deploying databases on containers, organizations are taking multiple approaches. The survey found Database-as-a-Service (DBaaS) offerings from cloud vendors is the most popular approach, with 61% of respondents utilizing these offerings. Database-as-a-Service is an API-based cloud service model where the service provider is responsible for the required database physical infrastructure and server-side DBMS resources, including performance configurations — essentially simplifying administration. Following close behind DBaaS offerings is deploying cloud-native databases such as Crunchy Data, Couchbase, MongoDB etc., with 52% of respondents reporting use of these offerings.
When asked about how their organization plans to consume databases in two years from now, results were similar but show an increase in both the respondents that plan to deploy a cloud-native database and those that plan to consume a DBaaS offering from independent database vendors. Respondents that plan on connecting to databases outside containers and Kubernetes are decreasing — suggesting more organizations want to adopt databases on containers and Kubernetes.
Databases are everywhere – including the edge
Edge computing has been unlocking new opportunities for organizations to deliver new insights and experiences. As important data-related decisions are happening at the edge, organizations are reconsidering where data will be stored, given privacy and security and compliance considerations.
A majority of respondents (63%) are currently deploying or planning on deploying databases on containers and Kubernetes at the edge. Of those who plan to deploy databases on containers and Kubernetes at the edge, almost three-quarters (74%) plan to use it for either data analytics or AI/ML inferencing at the edge. In contrast, only 18% reported they need an operational/transactional database for an application at the edge.
The need for hybrid
Databases and data analytics are integral to cloud-native applications, accelerating data ingestion, storage, processing and analysis. Containerized databases have now become an on-demand utility that is integral to the application itself.
Kubernetes users are frequently mixing multiple methods of integrating data services into their clusters, with a combination of cloud databases, databases deployed directly through Kubernetes and also connecting to VMs running data services outside of the cluster. A platform that enables all three is key to developer agility.