For decades, multidimensional databases have powered some of the most important analytical applications in the enterprise.
Financial planning. Management reporting. Profitability analysis. Forecasting. Operational analytics. Complex business calculations.
Platforms such as Oracle Essbase and Microsoft Analysis Services helped establish the multidimensional model as an effective way to organize and analyze complex business data. However, the data platform around them has changed.
Organizations are increasingly consolidating enterprise data in cloud platforms such as Snowflake. Compute and storage are elastic. Data can be governed centrally. SQL is ubiquitous. And AI is changing how people expect to interact with business information.
Yet many organizations still rely on a separate generation of OLAP infrastructure to provide multidimensional analytics.
Casabase Cube was built to change that.
What Is Casabase Cube?
Casabase Cube is a modern, cloud-native OLAP engine built natively on Snowflake.
It brings multidimensional modeling, hierarchical analysis, business calculations, and high-performance analytical querying directly to data stored in Snowflake, without requiring a separate OLAP server or proprietary analytical database.
Organizations can create cubes, dimensions, hierarchies, calculations, and business models while keeping the underlying data within Snowflake.
The result is an analytical environment that combines the familiar capabilities of enterprise OLAP with the scalability, security, governance, and openness of a modern cloud data platform.
Multidimensional Analytics Without a Separate OLAP Platform
Traditional OLAP architectures typically introduce another layer into the data environment.
Data is extracted from enterprise systems, loaded into an analytical database, transformed into cubes, aggregated, and maintained separately from the organization’s broader data platform.
Casabase Cube takes a different approach.
It runs as a Snowflake Native Application and operates directly within Snowflake.
There are no separate OLAP servers to deploy and manage. There is no proprietary analytical database to maintain. And there is no need to move enterprise data outside Snowflake simply to make it available for multidimensional analysis.
Casabase Cube performs aggregation and calculations dynamically at query time, allowing organizations to analyze current Snowflake data without maintaining traditional pre-aggregated cube structures.
How Casabase Cube Can Help Your Organization
For organizations already using Snowflake, Casabase Cube can simplify the analytical architecture considerably.
Instead of operating Snowflake alongside a separate OLAP platform, multidimensional analytics can become part of the Snowflake environment itself.
Consolidate Your Analytical Architecture
Many enterprises maintain multiple layers of analytical technology.
A cloud data platform stores enterprise data. An OLAP platform provides multidimensional analysis. BI platforms provide visualization. Additional systems may provide planning, reporting, or AI capabilities.
Every additional platform introduces infrastructure, integrations, security controls, data pipelines, administration, and specialized skills.
Casabase Cube allows the multidimensional layer to run where the data already lives.
This can reduce infrastructure requirements, simplify data movement, and eliminate an entire class of traditional OLAP server administration.
Keep Business Logic Close to Your Data
Enterprise analytical applications often contain years of accumulated business knowledge.
Account hierarchies. Organizational structures. Alternate rollups. Financial formulas. Variance calculations. Ratios. Allocations. Dynamic calculations.
Those models are valuable, even when the technology hosting them has become difficult to maintain.
Casabase Cube provides multidimensional modeling capabilities designed to represent sophisticated enterprise models, including hierarchies, alternate and shared members, dynamic member formulas, calculated members, two-pass calculations, and solve order.
Organizations can preserve the multidimensional structures that make their applications useful while moving them onto a modern data architecture.
Query Multidimensional Data with SQL
Traditional OLAP systems frequently require specialized query languages, APIs, or reporting tools.
Casabase Cube makes multidimensional data accessible through standard SQL.
That means Cube results can participate naturally in the broader Snowflake ecosystem and can be consumed by technologies organizations already use, including Power BI, Tableau, Alteryx, Microsoft Fabric, Python, and other SQL-compatible tools.
Casabase Cube also provides a Query Builder for users who want to construct multidimensional queries without writing SQL.
Analyze Data in Real Time
Traditional cubes frequently depend on data loads, aggregation processes, calculation scripts, or cube rebuilds before updated information becomes available.
Casabase Cube uses a query-time calculation and aggregation architecture.
Rather than maintaining large sets of precomputed aggregations, results can be calculated dynamically against Snowflake data.
This makes it possible to build multidimensional analytical applications around current enterprise data while taking advantage of Snowflake’s scalable compute architecture.
Make Multidimensional Data AI-Ready
AI is creating another important shift in enterprise analytics.
Natural-language analytics become far more valuable when an AI system understands not only tables and columns, but also the business meaning behind the data.
Casabase Cube models can provide structured business context such as dimensions, hierarchies, measures, relationships, and calculations.
Through integration with Snowflake Intelligence, organizations can make governed multidimensional business models available for natural-language exploration and AI-powered analytics without building a separate AI data architecture.
Casabase Cube vs. Oracle Essbase and Microsoft Analysis Services
Casabase Cube shares an important idea with platforms such as Oracle Essbase and Microsoft Analysis Services:
Complex business data is often easier to understand through a multidimensional model.
The difference is how that model is implemented. Traditional OLAP platforms were designed for an era when specialized analytical servers were necessary to deliver acceptable performance.
Casabase Cube was designed for a cloud data platform where scalable compute, centralized storage, SQL access, governance, and AI capabilities already exist.
| Traditional OLAP | Casabase Cube | |
|---|---|---|
| Architecture | Separate OLAP platform | Snowflake Native Application |
| Data location | Data typically copied into cubes/models | Data remains in Snowflake |
| Infrastructure | Dedicated analytical servers/services | Runs within Snowflake |
| Aggregation | Often relies on processing or pre-aggregation | Dynamic query-time aggregation |
| Calculations | Proprietary OLAP calculation engines | Multidimensional calculations within Snowflake |
| Query access | Specialized languages and APIs often required | Standard SQL and Query Builder |
| Scaling | Dependent on OLAP infrastructure | Uses Snowflake compute |
| Security and governance | Separate security model often required | Leverages the Snowflake environment |
| Integration | Platform-specific integrations | Snowflake ecosystem and SQL-compatible tools |
| AI | Typically requires additional integration | Designed for Snowflake Intelligence |
For organizations running large Essbase or Analysis Services environments, this distinction can be significant.
Modernizing OLAP no longer has to mean simply moving the same server-based architecture to newer infrastructure.
It can mean eliminating the separate OLAP infrastructure altogether.
A Modern Alternative to Oracle Essbase
Essbase has been particularly influential in financial and enterprise analytics, and many organizations have invested heavily in Essbase applications over decades.
Those applications often contain sophisticated outlines, hierarchies, member formulas, shared members, calculation logic, and business rules that cannot simply be replaced by a collection of relational tables.
Casabase Cube is designed to provide a migration path that preserves the value of multidimensional modeling while changing the underlying architecture.
Existing Essbase applications can be migrated using their native outline and level-0 data artifacts, allowing organizations to move established analytical models into Snowflake rather than redesigning them from scratch.
Once migrated, the model becomes part of a Snowflake-native analytical environment rather than another analytical system operating beside it.
What About Analysis Services?
Microsoft Analysis Services addresses many of the same fundamental problems as Essbase, particularly multidimensional modeling, semantic modeling, calculations, and business-oriented analytical structures.
Casabase Cube approaches those requirements from a Snowflake-first perspective.
For organizations standardizing their enterprise data architecture around Snowflake, this can eliminate the need to maintain a separate Microsoft analytical engine simply to provide a semantic or multidimensional layer over enterprise data.
The objective is not to abandon multidimensional analytics. It is to modernize the architecture underneath it.
From OLAP Servers to an OLAP Engine
That distinction captures much of what motivated us to build Casabase Cube.
The multidimensional model remains extremely useful, but what has changed is the infrastructure required to deliver it.
Organizations should not necessarily need a separate analytical database, specialized server infrastructure, duplicated enterprise data, proprietary query languages, and lengthy aggregation processes simply because their business requires hierarchical analysis and sophisticated calculations.
Modern cloud data platforms have changed what is possible.
Casabase Cube brings the OLAP engine to the data instead of moving the data to the OLAP server.
The Next Generation of Multidimensional Analytics
We believe multidimensional analytics still has an important role to play in the modern data stack, but it should work naturally with the platforms enterprises are building around today.
That means operating directly on cloud data. Using elastic compute. Integrating with standard SQL tools. Participating in enterprise governance. Supporting sophisticated business calculations. And making those business models available to a new generation of AI-powered analytics.
That is what we built Casabase Cube to do.
The architecture underneath multidimensional analytics is changing. Casabase Cube provides the path forward.
Ready to See What Modern OLAP Looks Like?
Casabase Cube brings enterprise multidimensional analytics directly to Snowflake, without the infrastructure and complexity of a traditional OLAP platform.
Explore Casabase Cube to learn how you can modernize existing Oracle Essbase, Oracle Cloud EPM, or Microsoft Analysis Services applications or build new multidimensional analytical applications directly on Snowflake.