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        Matt Aslett's Analyst Perspectives

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        Couchbase Modernizing Relational Database Workloads

        The term NoSQL has been a misnomer ever since it appeared in 2009 to describe a group of emerging databases. It was true that a lack of support for Structured Query Language (SQL) was common to the various databases referred to as NoSQL. However, it was always one of a number of common characteristics, including flexible schema, distributed data processing, open source licensing, and the use of non-relational data models (key value, document, graph) rather than relational tables. As the various NoSQL databases have matured and evolved, many of them have added support for SQL terms and concepts, as well as the ability to support SQL format queries. Couchbase has been at the forefront of this effort, recognizing that to drive greater adoption of NoSQL databases in general (and its distributed document database in particular) it was wise to increase compatibility with the concepts, tools and skills that have dominated the database market for the past 50 years.

        Couchbase was created in 2011 through the merger of two companies founded a couple of years earlier to build businesses based on the Apache CouchDB document database and the Memcached distributed in-memory caching system, respectively. This combination of functionality was integral to Couchbase’s distributed document database architecture and has also been reflected in the company’s culture of fusing together multiple concepts to deliver a flexible and adaptable data platform that can be used to support a variety of data workloads, both on-premises and in the cloud.

        Today, Couchbase offers Couchbase Server for deployment on-premises and in the cloud, as well as Couchbase Mobile for edge devices and locations, and the recently rebranded Couchbase Capella database-as-a-service offering. Regardless of the deployment location, Couchbase serves as a data platform for agile and distributed data processing to support interactive applications. The company has attracted approximately 550 customers which contributed to revenue of over $100 million for the year ending January 31, 2021, and fueled the company’s initial public offering in July 2021. Couchbase has well-known customers including the likes of Comcast, eBay, PayPal, Pfizer, United and Wells Fargo.

        Ventana_Research_Benchmark_Research_Analytics_06_Platforms_20211025-1Like most NoSQL vendors, the company’s success has been driven by the development of new applications designed specifically to take advantage of flexible schema and distributed architecture. This has enabled the various NoSQL database providers to gain a toehold in the database market. Almost one-quarter (22%) of respondents to Ventana Research’s Analytics and Data Benchmark Research are using NoSQL databases in production today. However, the company has also recognized that in order to appeal to a wider set of customers and potentially replace existing relational databases, it needed to support concepts and technologies that are familiar to developers and database administrators who are more used to working with relational databases. The culture of fusing multiple approaches has included embracing relational database concepts, and even the SQL query language.

        Application developers have been instrumental in driving adoption of NoSQL databases, taking advantage of flexible schema to accelerate development by avoiding the need to predefine table schema. As adoption has grown and become more strategic, however, there is an increasing need for database administrators and other IT staff to manage and work with NoSQL databases. As such, NoSQL databases have evolved to reflect the skills used to interact with relational databases and analytics tools. Couchbase has been an instigator of this approach through its development of the SQL++ specification, which can best be thought of as an extension to SQL that enables users to apply their SQL skills to query and manage data stored in the JSON format. SQL++ is implemented by Couchbase via its N1QL for Analytics query language. Couchbase Server 7, launched in July, delivered improved support for transactional applications via the addition of N1QL’s support for multi-document distributed SQL transactions.

        This approach of providing familiarity with relational concepts has been boosted by the addition of other new features in Couchbase Server 7. Specifically, Couchbase Server 7 added the concept of managing data stored in Couchbase in Scopes and Collections, which can be thought of as the equivalent to the relational concepts of ”schema” and ”tables.” Scopes and Collections are designed to enable improved organization, management and indexing of data with Couchbase. However, they can also be used to map existing relational database workloads to Couchbase for potential migration. This could be critical to the company’s ability to tap into opportunities for expansion within its customer base, as well as attract new customers, as organizations consider their options for new interactive applications. We assert that through 2024, six in 10 organizations will re-examine their current operational database suppliers with a view of supporting more agile and intelligent operational applications and improving fault tolerance.

        VR_2021_Data_Operational_Database_Assertion_1_Square-1In addition to being available for self-managed deployment on-premises and in the cloud, Couchbase Server 7 also forms the basis of Couchbase Capella, the company’s new database managed service. Launched in October, Couchbase Capella replaces the previous Couchbase Cloud offering, which was installed in a customer’s own virtual private cloud environment. In comparison, Capella is a full-managed database-as-a-service offering that provides capabilities for managing data across multiple regions, with multi-cloud support in the works (Capella is initially only available on AWS, but support for other clouds is in development). As we recently noted, there are multiple drivers for multi-region and multi-cloud database capabilities, one of which is workload isolation. This could be important for supporting regulatory requirements to retain data in a specific geography, but also for separating workloads that could compete for resources. Although Couchbase is primarily used as an operational data platform, as Ventana Research delineates the market, it can also support real-time query or analytics. With Couchbase’s workload isolation capabilities, organizations can replicate data across multiple nodes and dedicate individual nodes in the cluster to specific workloads on the same data, such as operational serving, indexing, event processing, full-text search and analytics.

        The breadth of functionality offered by Couchbase Server 7 and Couchbase Capella is indicative of how much NoSQL databases have evolved in recent years. Although organizations that have adopted NoSQL databases are still in the minority compared to incumbent relational databases, the proportion of workloads that are entirely unsuitable for NoSQL databases diminishes with each new release. Just as relational database vendors have added support for storing and processing JSON documents, so have NoSQL database providers added support for relational concepts. The line between SQL and NoSQL databases is increasingly blurred. Being capable of supporting workloads traditionally deployed on relational databases is one thing; organizations actually migrating workloads from relational to NoSQL databases is quite another. However, Couchbase has made a considerable effort to introduce features and functionality that meet SQL developers where they are – allowing them to apply their existing skills and tools to Couchbase, rather than having to learn unfamiliar languages and approaches. I recommend that organizations considering their potential database providers for both new operational applications and modernizing existing workloads should at least familiarize themselves with the current capabilities offered by NoSQL providers, especially Couchbase’s ”SQL-like” capabilities, as well as its support for transactions and relational concepts.

        Regards,

        Matt Aslett

        Matt Aslett
        Director of Research, Analytics and Data

        Matt Aslett leads the software research and advisory for Analytics and Data at ISG Software Research, covering software that improves the utilization and value of information. His focus areas of expertise and market coverage include analytics, data intelligence, data operations, data platforms, and streaming and events.

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