At Oracle OpenWorld 2019, Larry Ellison made a pledge that his company would bring to market the world’s first autonomous cloud: databases, infrastructure, and other IT services bundled in an integrated cloud computing fabric. Of course, the outspoken CTO/co-founder of the world’s largest database company is also infamous for publicly dismissing cloud computing as a fad in prior years. But to Ellison’s credit, Oracle’s central strategy these days revolves around its Oracle Autonomous Database — an all-in-one cloud database for data marts, data lakes, operational reporting, and batch data processing.
Whether they were first to market with the autonomous cloud is up for dispute, but one thing is for certain: as cloud databases become increasingly prevalent, Oracle faces an ever-expanding arena of competitors for the cloud database crown.
Cloud Databases Today
Market research firm IndustryARC predicts that the global cloud database market will reach $39.1 billion by 2026, at a CAGR of 31.4% between 2021-2026. This growth is attributed to the data explosion brought on by an onslaught of mobile and IoT devices, expanding cloud database adoption in sectors such as banking and education, and the overall growing popularity of database-as-a-service (DBaaS) — metered databases that are managed and scaled in the cloud.
5 Trends in Cloud Databases
The majority of the following trends deal with so-called “cloud-native” databases: databases deployed and delivered strictly through the cloud. Per the economic advantages of the cloud, many of the advanced computing and IT resources required by these newer cloud databases could only be acquired cost-effectively through a metered, time-shared usage model.
From the rise of autonomous cloud databases to increased graph database adoption, the following are five trends in cloud databases to keep track of in the near future.
1. Increasing Graph Database Adoption
Graph databases are a type of cloud-native, NoSQL database technology specially designed to focus on the relationships between data, as well as the data itself. Structurally, a graph databa se consists of nodes (circles) connected by edges (lines)— these represent data points and relationships, respectively.Â
Graph databases are becoming an increasingly popular cloud database option, as they don’t require rigid design and data structure formalities typical of standard relational databases. Leading solutions in this category include Neo4j and Amazon Neptune, to name a few.
2. Rise of Multi-Cloud Database Clusters
In a general cloud context, multi-cloud deployments enable firms to leverage several cloud vendors to achieve better performance, scalability and availability. The importance of this capability has become more apparent over the years as large swathes of the internet have experienced outages due to failures on the part of public cloud service providers.
New cloud database offerings such as MongoDB Atlas offer users the ability to run database-driven applications on several cloud infrastructures simultaneously — for instance, across AWS, Google Cloud Platform, and Microsoft Azure, allowing for multicloud high availability at the database level.
See more: Cloud Database Market 2021
3. Fully-Managed (Autonomous) Cloud Databases
As mentioned previously, Oracle’s early vision of a self-managing database capable of automated patching, upgrades, and tuning is now manifest in its Autonomous Database product. Not to be outdone, Microsoft’s Intelligent Insights enhances Azure SQL cloud databases with AI-powered features like proactive monitoring, automatic detection of issues, and self-tailored performance insights, to name a few. As more small and medium-sized organizations move their databases to the cloud, cloud-native solutions will at least need to become easier to manage — if not fully automated.
4. Legacy Database Products Becoming Cloud-Based
Well-established relational database products have started their migration to the cloud, with long-standing customers heavily invested in these early database technologies following suit. For example, IBM’s Db2 product, first released back in 1983, has been recently revamped as IBM Db2 on Cloud: a fully managed SQL database solution that runs in the cloud on a metered, pay-as-you-go basis.
5. More Streaming/Time-Series Database Deployments
According to the latest figures, over 26 billion IoT devices are currently churning out massive volumes of data: sensor readings, weather conditions, machine operating levels, patient health monitoring statistics, and a myriad of other telemetry types for various use cases. These data types are uniquely structured and tend to be immutable (i.e., the data is never updated, only stored) — think temperature readings regularly recorded over a period of time. Because the cloud databases optimized for this typically have their data “streamed in” and time stamped, they are referred to as, appropriately enough, time-series or streaming databases.
Vendors like InfluxDB and Prometheus are currently experiencing heightened demand as time-series databases come into vogue with expanding IoT adoption and the arrival of Industry 4.0.
ConclusionÂ
Despite their merits, cloud databases aren’t ideal for every organization. In many cases, strict data governance restrictions or compliance measures require data management and security to remain on premises. Firms operating under these constraints have only traditional database options to select from; that said, these same firms are likely to already benefit from cloud databases, albeit indirectly through the use of third-party SaaS applications.
