Standard Edition
Analytical database
The product for analysis and cross-database access.
- SQL analysis and aggregation
- Cross-database connections and queries
- Familiar tools such as DBeaver and pgAdmin
Korean commercial database
GooseDB.
GooseDB
Launch scheduleLaunch planned for early 2027
GooseDB.
Analytics + Vector & AI Database.
Connect distributed data for analysis, and retrieve business knowledge for AI answers. A commercial database developed in South Korea by ORASCOPE.
Closed-source commercial software
GooseDB is a commercial product, not open source.
Enterprise Edition
Analytics, vector search and AI database
Every Standard Edition capability, plus vector search, RAG and AI integration.
- All Standard Edition capabilities included
- SQL analytics and cross-database queries included
- Vector and keyword search
- RAG-based document Q&A and AI integration
| Capability | Standard Edition | Enterprise Edition |
|---|---|---|
| SQL analysis & aggregation | Included | Included |
| Cross-database access | Included | Included |
| Vector search · RAG · AI | — | Included |
GooseDB Standard Edition
Selling well.
But running out of stock?
Sales live in one system. Stock lives in another. GooseDB Standard Edition brings the data together so you can spot popular products with little stock left.
- Query different databases using a shared product code
- Compare recent sales and current stock in one result
- Analyze with familiar tools such as DBeaver or pgAdmin
GooseDB Enterprise Edition · RAG
Ask your company knowledge.
Skip the policy hunt.
“Can I book a £150 hotel for my London business trip?” RAG retrieves the relevant travel policy first and supplies it as context for an AI answer.
GooseDB Enterprise Edition retrieves the nightly limit and approval conditions. A connected AI model explains whether the booking needs approval, with the source policy available to check.
Inside GooseDB
A workspace for
analysis and operations.
The actual web console provides entry points for SQL editing, active sessions, server health and AI work.
GooseDB ConsoleActual capture · Earlier development version
GooseDB adoption
What we review
after you get in touch.
- 01
Discuss your needs
Tell us about your databases, tools and business need. We review whether analytics alone or search and AI are required.
- 02
Review sample data
Within an agreed scope, review connectivity and results using sample data and representative queries.
- 03
Discuss the deployment
Use the findings to discuss the edition, deployment environment, license and scope of support.
Use cases
Put it to work.
Standard Edition across business systems
Query information from different databases through one access point. Evaluate it with the SQL tools you already use.
Finding business knowledge
Build search that finds related content even when the exact term is forgotten. Use keyword search for product names and error codes.
AI grounded in company knowledge
Use RAG to find relevant policies and manuals for AI answers. Build workflows that let teams check answers against source material.
How it connects
See how it
fits together.
GooseDB Standard Edition provides SQL analysis, aggregation and cross-database access. GooseDB Enterprise Edition includes the same analytical and database-access capabilities, with vector and keyword search and AI integration added.
Explore the system diagram
FAQ
A few things
worth knowing.
Is GooseDB open source too?
No. GooseDB is a closed-source commercial database developed in South Korea by ORASCOPE, provided under a separate commercial license. It is distinct from the Apache 2.0 open-source projects herdr-tower and Parallax Browser.
Which product should we choose?
Choose GooseDB Standard Edition for analysis and cross-database access. Choose GooseDB Enterprise Edition when you also need vector search and AI integration. Enterprise Edition includes the analytical and cross-database capabilities of Standard Edition.
Must we replace all our existing databases?
Not necessarily. You can start by evaluating queries against supported external databases. The appropriate scope depends on your data structures and business requirements.
Can we reuse our SQL and existing tools?
PostgreSQL-compatible connections let you use existing tools and drivers. This does not mean complete equivalence with every PostgreSQL feature. Validate the actual queries and tools during adoption.
How is vector search different from ordinary search?
Keyword search is useful for finding exact words. Vector search finds content with a similar meaning even when the wording differs. GooseDB lets you use these approaches for the work at hand.
What can we do with RAG?
Retrieve relevant passages from internal documents or manuals and use them in AI answers. GooseDB searches for content and sources; a connected AI model answers using the results. Searchable material and model connections must be prepared.
What is needed for the AI capabilities?
You need an Enterprise distribution and license configuration that includes the required features, a connected AI model and prepared data. Configurations using models hosted within your organization can also be evaluated.
What should we bring to an adoption discussion?
Describe your data sources, tools, data volume, deployment environment and the problem you want to solve. We can review feature needs, compatibility and license configuration together.
GooseDB
Plan your next
step with data.
Tell us about your data sources, environment and required features.