Databases and data analytics provide methods for ingesting, storing, processing, and analyzing datasets from a variety of sources for use cases such as, mobile and ecommerce applications, AI/ML, business intelligence, and more.
Why deploy databases and data analytics workloads on containers & Kubernetes?
- Agility - Deploy and manage modularized databases and data analytics workloads anywhere with speed, allowing faster project execution and more frequent updates.
- Elastic Scaling - Dynamic scaling of compute resources to meet the changing needs of databases and data analytics workloads.
- Portability - Containerize once, deploy and move anywhere.
Potential challenges
Potential executional challenges for databases and data analytics workloads on containers and Kubernetes.
- Downtime and data loss - Failures, outages, data corruption
- Operational complexity - Architecture and operations (e.g. containers, storage, networking, data protection), performance tradeoff
- Lack of ISV support - ISV endorsement or support documentation
- Lack of expertise - Gaps in skills and processes
Benefits of deploying databases and data analytics on Red Hat OpenShift
Automated operations
Kubernetes Operators simplify and automate the deployment, scaling, and lifecycle management of containerized databases and data analytics on Red Hat OpenShift. This helps enable DevOps, and allows Database Administrators (DBAs) to focus on more strategic tasks such as controlling user access and security.
Consistency and portability
Secure deployment, operations, and portability in a consistent way across the hybrid cloud. Run containerized databases and data analytics in the same manner as the other components of the cloud-native application(s).
Partnerships and integrations with ISVs
Red Hat has strategic partnerships and integrations with key database and data analytics ISVs such as Microsoft, Cloudera, MongoDB, Crunchydata, Couchbase, Starburst, along with Red Hat’s AMQ Streams (Kafka on Kubernetes) using Kubernetes Operators to help make our mutual customers successful.
Red Hat Marketplace
Simpler way to buy and deploy container-based software on OpenShift, including databases and data analytics workloads.
Scalable and resilient software-defined storage for running containerized workloads, including databases and data analytics.
Frameworks, integration, runtimes, programming languages. E.g. Red Hat AMQ streams (Apache Kafka on Kubernetes)
Robust and secure foundation for running databases and data analytics workloads on Red Hat OpenShift.