Querona documentation

Querona documentation#

Querona is a Data Fabric platform powered by data virtualization — a single, governed layer over your data, whether it lives in one system or many — queried and joined in real time, with no data movement. It runs entirely on your own infrastructure — on-premise, cloud, or hybrid — with no SaaS lock-in, so your data never has to leave your environment. Querona exposes your data through SQL Server–compatible, REST, GraphQL and MCP endpoints, with a full web interface for management and monitoring.

Start here

Quickstart — your first query in minutes

Connect a data source, create a virtual database, and run a single query that joins live data across systems — without copying or moving anything.

Open the Quickstart → I use SQL Server →

Choose your path#

For SQL Server users

Bring the T-SQL, SSMS, linked servers and BI tools you already know to your whole, diverse data estate — your skills transfer.

Querona for SQL Server users
For analysts & self-service

Just need the data? Query any source from Python or a notebook, and join huge corporate data with a small local set straight from Excel.

Querona for analysts and self-service
How Querona works

Data virtualization, architecture, and the virtual databases, tables and views at the heart of the platform.

Overview
Tutorials

Hands-on, end-to-end walkthroughs — start with querying a REST API with SQL.

Tutorials
Install & deploy

Requirements, prerequisites, installation, upgrade and post-install configuration.

Installation
Build data solutions

Connect sources, model virtual databases, materialize for speed, mask data and publish it.

Build data solutions
Transact-SQL reference

The Transact-SQL surface Querona supports — statements, functions, data types, collations, JSON, XML and spatial.

Transact-SQL reference
Connect clients & BI tools

Power BI, Tableau, Excel, Python, R, and SQL Server linked servers.

Client Connectivity
Open data endpoints

Expose virtual databases over REST, GraphQL and MCP, alongside the SQL Server (TDS) endpoint.

Open data endpoints
Administer & monitor

Engine and instance configuration, jobs, Spark, monitoring, security and access rights.

Administration
Browse connectors

Relational, NoSQL, big data, SaaS, file and generic (ODBC / JDBC / ADO.NET / OLEDB) connectors.

Data sources
Reference

System catalog views, dynamic management views, system stored procedures and error codes.

Reference

Why Querona#

As a Data Fabric platform, Querona provides an abstraction layer for all data to achieve flexibility for change, pervasive and consistent data access, and greatly reduced costs because there is less need to create physically integrated data structures. It lets organizations change and optimize how data is processed and physically persisted, without impacting applications and business processes.

  • Runs entirely on your infrastructure. On-premise, cloud, or hybrid — on servers you control. Your data never has to leave your environment, with no mandatory cloud service and no SaaS lock-in.

  • Express it in SQL. Model your solution as SQL views over your sources — one declarative model Querona maintains, refreshes and re-engines for you — instead of a web of pipelines and connectors to operate and keep in sync.

  • Real-time federation. Query and join heterogeneous data sources in real time, with no data movement and no up-front ETL.

  • Materialization when you need speed. Materialize hot views using multiple strategies — full, incremental, in-memory and physical table rotation — to accelerate selectively instead of warehousing everything.

  • SQL Server–compatible. A SQL Server–compatible endpoint, metadata catalog, system views, stored procedures and T-SQL, so your existing drivers, tools and BI clients just work.

  • Open access endpoints. Expose data through SQL Server (TDS), REST, GraphQL and MCP endpoints — for applications, modern web and mobile clients, and AI agents alike.

  • Full web interface. Manage, configure and monitor the entire platform from a browser-based GUI.

  • Broad connectivity — relational, NoSQL, big data, SaaS and files through native, ODBC, JDBC, ADO.NET and OLEDB providers — with a high-performance columnar engine and built-in Apache Spark for processing and materialization.