CloudQuant Data Liberator revolutionizes time series data management with a zero-copy architecture that reduces costs while improving security and performance. Purpose-built for the complexities of investment and trading data, Data Liberator replaces fragmented, expensive data stacks with a unified platform.
Connect directly to your existing databases, data stores, or file systems, no matter where they are, without moving or duplicating data. Reduce infrastructure costs and eliminate ETL complexity.
Purpose-built for financial data with point-in-time accuracy, temporal queries, and seamless handling of high-frequency datasets across any time horizon.
Granular entitlements, full audit trails, and role-based access controls ensure compliance while enabling secure data sharing across teams and external partners.
Modern REST APIs integrate seamlessly with Python, R, SQL tools, and BI platforms, from research to production—same interface, same security model.
Smart indexing and query optimization deliver fast response times without repeatedly fetching from the original remote sources or impacting underlying systems.
Filter massive amounts of data on the server side, where bandwidth is in abundance, and only pull down the data you want with Full ANSI SQL Query compatible language support
"Liberator enables rapid, direct access to secure time-series data with just one line of code. It streamlines the process for analysts, eliminating reliance on IT teams and providing advanced security features for efficient data management in a modern environment."
Python, including Jupyter Notebooks and JupyterLab:
An automated tool that allows data analysts to locate other datasets containing related information
Web wizards that allow data publishers to self-publish datasets to their own data.
