Fully managed multidimensional analytics with AI-assisted workflows, natural-language exploration, and planning in Excel.
Oracle Essbase is available as a fully managed service on Oracle Autonomous AI Lakehouse in OCI, AWS, Microsoft Azure, and Google Cloud. You can run Essbase in your preferred cloud while keeping familiar models and tools.
For existing Essbase customers, this brings a managed cloud foundation and database services such as automated backup and recovery to the analytical capabilities you already use. For Oracle database and lakehouse users, Essbase adds business modeling, financial and time intelligence, and interactive what-if analysis. You can compare actuals with budgets, explore results in Excel, and write revised planning values back to your Essbase model.
AI offers new ways to build and explore these models. AI Cube Builder uses your intent and relational data to propose a model you can review and refine through an intuitive interface. Compatible AI assistants let you ask business questions in natural language and explore results using the dimensions, hierarchies, and calculations defined in Essbase.
Build business models with AI and explore them in natural language
AI Cube Builder analyzes your relational model and uses your intent to propose dimensions, hierarchies, and measures for an Essbase cube. You can review and refine the proposed model before building the cube. Its simple, intuitive interface lets you create cubes without prior knowledge of Essbase interfaces.
Once the model is ready, ask a question such as “Which products contributed most to the revenue variance in the West region last quarter?” The assistant can use Essbase tools to query the cube and help explain the results in the context of its dimensions, hierarchies, measures, and calculations.
For existing applications, these workflows use the business definitions your teams already maintain. Compatible AI tools can help analyze and present results as visualizations or interactive dashboards, while Essbase provides the multidimensional model and calculation logic behind the analysis.
Through the Essbase MCP Server, AI clients that support the Model Context Protocol (MCP) standard can work with Essbase applications, metadata, calculations, and data over authenticated connections. MCP access profiles control the available tools, while Essbase permissions govern the operations each user can perform.
Run Essbase on a fully managed cloud foundation
Essbase data and metadata are managed in the database, while Essbase continues to manage the multidimensional model, calculations, business rules, and analytical data flow customers already know.
This gives Essbase applications the data-management capabilities of Autonomous Database Serverless: built-in availability and reliability services, automated backup and recovery, security controls, encryption, and database administration that is managed by Oracle.
Customers no longer need to separately operate the Essbase infrastructure, filesystem storage, and underlying relational storage layer that support the application.
Build analytical models with Oracle database and lakehouse data
Build an Essbase model from Oracle database data to organize sales by Product, Market, and Time, with shared definitions for revenue, margin, and period comparisons. Users can pivot and drill through results using a consistent set of calculations and hierarchies.
Autonomous AI Lakehouse extends this approach to external data, including Apache Iceberg tables. Through supported integration and loading workflows, you can bring that data into Essbase applications and use the same multidimensional analysis and business calculations.
Add multidimensional analysis and writeback to your analytics
For database and lakehouse users, Essbase adds calculations and interactions that support planning, forecasting, and financial reporting. You can compare actuals with budgets, calculate year-to-date results, and explore a forecast across products, markets, and time periods using a consistent business model.
With writeback, authorized users can update planning values in the model. A planning team can revise a monthly forecast in Smart View for Microsoft Excel, save the changes, and use the application’s calculations to see how the revised plan affects results. This connects analysis with planning decisions.
Keep the Essbase experience you know
Essbase remains Essbase. Users continue to work with dimensions, hierarchies, calculations, financial intelligence, time-based analysis, and multidimensional navigation. Teams can continue to use MDX and the calculation capabilities they rely on, while business users keep the familiar Smart View experience in Microsoft Excel.
For existing customers, this is an evolution of the platform rather than a replacement for the analytical model. The business logic and multidimensional concepts that make Essbase valuable remain central to the experience.
Scale when your business needs it
Essbase workloads are rarely constant. Financial close, budgeting, forecasting, reporting cycles, and ad hoc analysis can all create periods of higher demand. With Autonomous Database underneath Essbase, applications can benefit from managed capabilities such as workload management, parallel database processing, automated optimization, and elastic compute.
The result is a more flexible foundation for applications with large or frequently changing datasets.
Get started
Enable Essbase in your Autonomous AI Database environment and start with one business question. New users can build a model from relational data with AI Cube Builder. Existing customers can validate a representative application, then connect a compatible AI assistant to explore its results.
Explore Essbase on Autonomous AI Lakehouse