Issue link: https://resources.awscloud.com/i/1496542
©2020 IDC #US47078920 7 Ledger Data Management (Amazon QLDB) Blockchain introduced the idea of a commonly managed, immutable, and trusted transaction manager. Blockchain works great when many entities wish to exchange items in an irrefutable way but provides no means of auditing or reporting on such exchanges because to do so would compromise the anonymity of the users. For internal use in enterprises, where the ultimate owner of all such exchanges is the enterprise itself, this is not a concern, so a ledger data management system makes perfect sense for use instead of blockchain. Amazon Quantum Ledger Database (QLDB) is such a facility, maintaining a transparent, immutable, and cryptographically verifiable transaction log that maintains a verifiable history of all changes to data. As such, QLDB provides data lineage and immutability as integrated features of the transaction log — placing data integrity as an incontrovertible outcome of data storage. QLDB is also serverless, so the client only pays for what is used. FUTURE OUTLOOK IDC research has shown that most enterprises are only in the beginning stages of their journey to the cloud. Many of these are looking at alternatives to the data management technologies they have been using up to now. Right now, they are looking to stage that transition through hybrid cloud configurations, but over the next five years, we can expect to see large quantities of product data shifting to the public cloud. Facilities such as those described in this white paper are already driving major applications in the cloud. As larger enterprises, which to date have mostly focused on hybrid cloud deployments due to the complexity of their application environments on-premises, move their production data to the cloud, these services are likely to be the workhorses of a good portion of such enterprise data in the future and provide a suitable environment for the born-in-the-cloud applications to follow. CHALLENGES/OPPORTUNITIES AWS is not alone in offering a public cloud platform with integrated data management services. AWS will be challenged to continue to develop its data management offerings in ways that achieve competitive advantage. Some users and third-party application developers are opting for third-party cloud database services, rather than committing to any public cloud platform for such services, to maintain independence. It is up to AWS to demonstrate that the integrated, fully platform-managed approach to database services is superior to any other option, both now and in the future, and to offer good compute, storage, and networking building blocks for cases where the selection of AWS database services doesn't fit an application's needs. CONCLUSION Database management systems have been around for a very long time and have continually evolved to address the changing needs of users. As enterprises embrace cloud architectures and data- intensive workloads such as IoT ingestion and processing, smart mobile device data, log data, other streaming data, complex graphs, and time series data, in addition to the data that fits neatly in the relational domain, they are moving to adopt a variety of database models, each attuned to the needs of the application and its data. It only makes sense that while some applications are best served using multimodel database systems, most others should employ purpose-built DBMSs that deliver the best performance characteristics for the application. If an enterprise is planning to use a range of DBMSs that support differing models, that enterprise should also do so within a framework that enables the management and governance of data across those DBMSs.