Instant insights. Zero perp.
With Dadroit Q, there is no need for complex data ingestion or indexing steps. Our in-memory engine accesses CSV and other standard formats directly, enabling near-instant filtering, finding, and SQL queries, no database imports required. This streamlined approach keeps your focus on meaningful analysis rather than setup.
Powered by DD®.Leading raw data query engine.
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Highlight importance. Redact sensitive ones.
Highlighting and redacting features in a data viewer are essential tools for managing sensitive information and emphasizing critical data points. Highlighting allows users to visually mark key values, trends, or insights, making it easier to identify and analyze important details at a glance.
Filter out the noise.
The filter functionality in a data viewer is a powerful tool that allows users to efficiently narrow down large datasets to focus on specific information of interest. By applying customizable criteria such as numeric ranges, text matches, date filters, or logical conditions, users can quickly identify patterns, trends, or anomalies without sifting through irrelevant data.
Stack Your Searches.
Uncover complex patterns by mixing and matching search and filter criteria in real time. Multi refiner lets you build a chain of operations—filtering specific columns, highlighting keywords, and more—so you see exactly what you need in seconds. Enjoy clear, actionable information without extensive setup or importing processes.
Limit Find or Filter to only selected columns.
Redact sensitive information. Pass the file with confidence.
On-the-Fly SQL for Massive Datasets.
Bring the full power of SQL to your raw datasets. There’s no need to import into a separate system or create special indexes, just open your file and start writing queries. It’s a quick, efficient way to discover insights hidden in even the largest data files, all while staying fully offline.
Your Data in Multiple Dimensions.
Create unique slices of your data by saving filters, find operations, and queries in separate Views. Flip between these pre-built perspectives in an instant, then export them all in one go. It’s a simple, efficient way to transform a single dataset into multiple targeted data scopes.
- This test reflects the approximate file load performance difference between Notepad++, Sublime, VSCode, and Dadroit JSON Viewer. This test was conducted using a machine with Intel® Core™ i9-9900K Processor, 32GB of RAM, and 256GB SSD on a 64-bit Operating System. The test file was generated using JSON Generator by Dadroit.↩
- In the test context, practicality means the ability to open a file and work with it in a reasonable time and machine. All testing was done trying to be honest and reproducing real-life use cases.↩