GoodData has been in the modern analytics ecosystem for some time. While it started out with a user-oriented business intelligence (BI) and hosted data warehouse approach, the company settled into the business of embedded/private-label ("OEM") analytics, essentially empowering its customers to provide analytics in their own applications to their own customers. And, while several BI players have eventually pivoted to that model as a way to augment their offerings, GoodData has specialized in it, and has powered analytics functionality for over 150K customers in the travel, healthcare, retail and other verticals. In short, GoodData has built a healthy business in the very crowded BI space. So why change things?
Well, to begin with, some customers will have some applications, often for in-house use, where cloud-hosted analytics won't cut it. For reasons of regulatory compliance, the public cloud may be off limits for their data, or the data needs to remain in specific geographic jurisdictions that the public cloud cannot guarantee or accommodate. Even if such scenarios are limited, and cloud-based solutions work for a great majority of a customer's requirements, it still means using a different analytics stack in those particular cases, which complicates maintenance and management of solutions.
There's more to it, though. A lot of BI solutions have their natural center of gravity around a heavy desktop application (even if it's browser-based -- it's still a desktop app in character) for exploratory work, and then a completely different modality for embedded solutions. This translates to the billing model, too: many BI solutions are based on monthly cost per user (or "seat" in industry parlance), whereas GoodData's domain-based billing would make much more sense.
With this in mind, GoodData is announcing its new cloud-native solution, aptly named GoodData Cloud Native (or GoodData.CN, for short). In a briefing with ZDNet, GoodData Founder and CEO, Roman Stanek, explained that the new release lets the company shift from its longstanding OEM model to the Data as a Service model, which accommodates customer-facing and in-house scenarios with a single architecture, based on microservices and container technology like Docker, Kubernetes and Helm. This allows the GoodData platform to run not only on any public cloud, but in private and hybrid cloud scenarios as well, and with 100% consistency of APIs and operations, across environments.
The GoodData.CN platform is based on three pillars: the analytics microservices themselves (which the company calls its "headless BI" layer), the React-compatible analytics APIs in a middle tier, and user interfaces, which may accommodate exploratory analytics, augmented analytics or embedded analytics. Whether a customer is embedding analytics functionality in its own applications running in the cloud, or using an ad hoc exploratory analytics application within its own firewall, the same APIs are called and the same data sources -- including data warehouse platforms like Snowflake, Microsoft's Azure Synapse Analytics, Amazon's Redshift and Vertica -- are available.
Developers are VIPs
GoodData even expects an ecosystem to emerge where third parties build their own UIs over the GoodData.CN platform. With that in mind, the company is launching a free Community Edition of the platform and will be open sourcing much of its own UI library. The Docker image-based Community Edition will be free for non-production use and allows for unlimited data volume, unlimited number of users, and free community support. Freemium, Growth, and Enterprise editions are the stepping stones from Community Edition/development scenarios into production use cases.
We're used to seeing self-service, desktop-centric BI services add embedded use cases to their bag of tricks as an afterthought. GoodData has mastered OEM scenarios, though, and is now adding support for in-house, ad hoc analytics to cover the full universe of use cases. In so doing, it's not looking to define its identity or business model but, rather, to build on it, applying what it has already been doing in the realm of BI infrastructure and making it available to a broader audience. Container technology makes it technologically possible and a strong core business makes it a prudent and sensible next step.