In this comparison, we outline the key differences between Fluent and Databricks Genie, answering questions about the types of users each solution is designed for, their technical differences, and their scalability within an organisation.
#2: Accuracy-First vs. Answer-First
Fluent crucially will only generate answers if the underlying logic has been defined by the data team and clarifies queries before responding. This makes it an ideal self-serve solution that a data team can trust to not feed business users hallucinations or guessed answers. Genie prioritises first-time answer generation, which is great for data professionals iterating on SQL to build dashboards but is less suitable for business users unfamiliar with underlying raw code.
#3: Flexibility vs. Vendor Lock-In
Genie only uses internal logic and terminology that the data team have manually introduced, known as a ‘locked-in’ solution. Fluent integrates with internal and external data sources, like your semantic layer or data catalog, enabling you to apply pre-existing business logic no matter where it’s stored. If you're confident that Databricks is the only data solution you want to use, Genie may be ideal for you, but if you work across multiple data tools, you may prefer the flexibility Fluent offers.
#4: Adaptable Metrics vs. Rigid SQL Queries
Fluent uses a semantic layer of metrics defined by the data team. This foundational set of ‘blueprints’ is used by the LLM to answer a broad range of data questions in plain English. Genie answers questions using exact SQL queries, which are very specific directives - ideal for data professionals who know exactly what to ask, or are searching for an existing query, but difficult to leverage for anyone non-technical.
