Try our Interactive Demos
With Q-Sensei’s analytics platform, hyper-precise searching,
exploring and correlation of billions of data points becomes easy.
See how we add value to data.
Try our Interactive Demos
With Q-Sensei’s analytics platform, hyper-precise searching, exploring and correlation of billions of data points becomes easy. See how we add value to data.
Hyper-precise Querying
Use our Query Builder to see value distributions per field
and build complex queries.
- 1,000s of Facets available with Dynamic Data Summaries
- Search, range search, and sort values within facets
- Select from Boolean operators and wildcards
Automated Outlier Detection
Choose between Standard Deviation, Box Plot, and Random Forest analysis.
- Benefit from Time Series graphs and Histograms
- Dive deeply into Outlier attributes and ratios
- Derive valuable insights from out-of-the-box visualizations
Hyper-precise Querying
Use our Query Builder to see value distributions per field
and build complex queries.
- 1,000s of Facets available with Dynamic Data Summaries
- Search, range search, and sort values within facets
- Select from Boolean operators and wildcards
Automated Outlier Analysis
Choose between Standard Deviation, Box Plot, and Random Forest analysis.
- Benefit from Time Series graphs and Histograms
- Dive deeply into Outlier attributes and ratios
- Derive valuable insights from out-of-the-box visualizations
See for
yourself
Streaming Data
Example: Amazon SQS
Hardware and Data Metrics
Q-Sensei Logs package (Q-Sensei Logs AWS Listing)
15 MB/day (AWS SQS), 30 days data retention, 260 Facets,
25 million data points
Application Log data
Data Lake
Example: Amazon S3
Hardware and Data Metrics
1 Standard Server (CPU: Intel Xeon E5-1650 v3 @ 3.50GHz (6 physical, 12 logical cores), RAM: 128GB, SSD: 500GB)
282 GB (JSON Format), 47 Facets, 9 billion data points
33 years of US Airlines Performance data from the United States Department of Transportation
See the difference in Analytical Search experiences using Q-Sensei versus Elastic/Kibana: Using the same data and the same hardware, Q-Sensei offers truly interactive Query support, full display of facets and facet values, as well as complex, multi-facet querying at blazing fast speed.
See for
yourself
Streaming Data
Examples: Apache Kafka, Amazon SQS
Hardware and Data Metrics
Q-Sensei Logs package (Q-Sensei Logs AWS Listing)
15 MB/day (AWS SQS), 30 days data retention, 70 Facets,
25 million data points
Application Log data
Data Lakes
Example: Amazon S3
Hardware and Data Metrics
1 Standard Server (CPU: Intel Xeon E5-1650 v3 @ 3.50GHz (6 physical, 12 logical cores), RAM: 128GB, SSD: 500GB)
282 GB (JSON Format), 47 Facets, 9 billion data points
33 years of US Airlines Performance data from the United States Department of Transportation
See the difference in Analytical Search experiences using Q-Sensei versus Elastic/Kibana: Using the same data and the same hardware, Q-Sensei offers truly interactive Query support, full display of facets and facet values, as well as complex, multi-facet querying at blazing fast speed.