Data modernization enables organizations to access enterprise data and extend the business value of core data that has been collected over many years. Data modernization is any initiative or process that results in more relevant and accurate data or more efficient and timely data delivery and analyses that support both improved governance (management, science, and enforcement) and serve industry and public needs.

This IBM® Redbooks® publication describes how to maximize the data serving capabilities on LinuxONE and how you can take advantage of these capabilities to modernize your enterprise.

We start by describing the value of using FUJITSU Enterprise Postgres on IBM LinuxONE and migrating your database to FUJITSU Enterprise Postgres on IBM LinuxONE. We present a database migration use case in 2.4, “Use cases: Migration from an Oracle Database system” on page 59.

We also describe using containers and the benefits of automation by using containers (see 3.2, “Benefits of automation when using containers” on page 99), and we describe how FUJITSU Enterprise Postgres on IBM LinuxONE can deploy databases quickly. We describe how database operations can be automated with FUJITSU Enterprise Postgres Operator. We also describe fluctuation in 3.5, “Fluctuation” on page 134.

In Chapter 4, “Application use cases: Geospatial processing” on page 155, we demonstrate geospatial processing when using PostGIS and FUJITSU Enterprise Postgres on IBM LinuxONE.

FUJITSU Enterprise Postgres on IBM LinuxONE supports PostGIS functions and on a high-performance platform with scalability and advanced security.

Chapter 5, “MongoDB as a service with Linux on IBM Z” on page 173 demonstrates the benefits of using IBM LinuxONE in your enterprise. This chapter describes how

IBM LinuxONE, combined with IBM Storage, provides high availability (HA), performance, and security by using a sample-anonymized client environment and includes a use case that demonstrates setting up a database as a service that can be replicated on a much larger scale across multiple client sites.

Chapter 1. Customer value

Chapter 2. Database migration

Chapter 3. Leveraging containers

Chapter 4. Application use cases: Geospatial processing

Chapter 5. MongoDB as a service with Linux on IBM Z

Appendix A. Converting SQL and PL/SQL to FUJITSU Enterprise Postgres SQL and PL/pgSQL

Appendix B. Additional data source information