Looker vs. Elastic Stack
A side-by-side comparison based on G2 review data.
| Metric | Looker | Elastic Stack |
|---|---|---|
| Overall rating | 4.4 | 4.5 |
| Review count | 1,653 | 109 |
| Ease of use | 8.5 | 8.3 |
| Ease of setup | 8.5 | 8.0 |
| Quality of support | 8.8 | 8.4 |
| Meets requirements | 8.9 | 9.1 |
| NPS | 58.653241 | 69.52381 |
| Small Business | 19.6% | 22.2% |
| Mid-Market | 60.3% | 43.5% |
| Enterprise | 20.1% | 34.3% |
| Total page views | 2,894 | 505 |
| Total LLM citations | 14,147 | 1,347 |
Looker
Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation.
- Ease of Use
- Insights
- Easy Integrations
- Integrations
- Data Visualization
- Analytics
Elastic Stack
The Elastic Stack, commonly known as the ELK Stack, is a comprehensive suite of open-source tools designed for ingesting, storing, analyzing, and visualizing data in real-time. It comprises Elasticsearch, Kibana, Beats, and Logstash, enabling users to handle data from any source and in any format efficiently. Key Features and Functionality: - Elasticsearch: A distributed, JSON-based search and analytics engine that allows for rapid storage, search, and analysis of large volumes of data.
- Ease of Use
- Log Management
- Versatility
- Search Efficiency
- Flexibility
- Dashboard Usability