Table of Contents
- Summary
- Cloud and Operational Databases Primer
- Report Methodology
- Decision Criteria Analysis
- Evaluation Metrics
- Key Criteria: Impact Analysis
- Analyst’s Take
- Methodology
- About Andrew Brust
- About GigaOm
- Copyright
1. Summary
Operational databases are the lifeblood of business computing and serve as the primary source of data used in analytics and machine learning. Classic relational database systems have run on-premises for decades, and many now run in the cloud, either natively or as adaptations of their on-premises forebears. With that shift, innovation has accelerated, and globally distributed operation of these systems is now feasible, even for smaller organizations.
Non-relational—NoSQL—databases, meanwhile, offer very low latency on writing data, which is what many business applications, and certainly a majority of large internet properties, need most. Whether recording new customers, orders, or just posted comments, these systems need to accept data quickly and provide users with a low-friction, high-satisfaction experience. Database schema flexibility is another hallmark of NoSQL databases, and as web and software development must become more nimble and adapt to change, the ability to augment or alter schemas without needing to take the database offline can be critical.
However, because of both the fundamental importance of their data and their continuing innovations that make them increasingly capable, modern, and versatile, traditional relational database systems remain relevant. These systems are rapidly acquiring capabilities previously associated with NoSQL databases, especially in the handling of unstructured data and new scale-out architectures. When combined with their traditional strong suit of broad and deep support for SQL, indexing savvy, query optimization and database consistency, the allure for customers to stay in the relational camp can be strong. And with relational systems gaining analytics and even machine learning (ML) capabilities, the value proposition gets even stronger.
In this Key Criteria report, we provide a primer for operational and cloud databases, covering the early days of both relational and NoSQL systems and a distilled summary of how they have evolved. We’ll also cover how the delineation between these two categories has blurred somewhat, and yet nonetheless persists, which assures that each category will in fact endure in the market. We’ll outline the table stakes, key criteria, emerging technologies, and evaluation metrics we believe customers should use to judge cloud and operational databases and make an informed, confident buying decision.
After reading this Key Criteria report, you’ll be ready to go on to our two Radar reports—one each for relational and NoSQL cloud and operational database systems—to review numerous vendor offerings in the space, get a sense of where each vendor’s strengths are, and then to go ahead with your platform decision.
How to Read this Report
This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding, consider reviewing the following reports:
Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.
GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.
Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.