MongoDB Atlas vs. Elastic Stack
A side-by-side comparison based on G2 review data.
| Metric | MongoDB Atlas | Elastic Stack |
|---|---|---|
| Overall rating | 4.5 | 4.5 |
| Review count | 906 | 109 |
| Ease of use | 8.9 | 8.3 |
| Ease of setup | 8.9 | 8.0 |
| Quality of support | 8.8 | 8.4 |
| Meets requirements | 9.0 | 9.1 |
| NPS | 70.409357 | 69.52381 |
| Small Business | 45.2% | 22.2% |
| Mid-Market | 25.9% | 43.5% |
| Enterprise | 29.0% | 34.3% |
| Total page views | 916 | 505 |
| Total LLM citations | 6,190 | 1,347 |
MongoDB Atlas
MongoDB Atlas is a developer data platform that provides a tightly integrated collection of data and application infrastructure building blocks to enable enterprises to quickly deploy bespoke architectures to address any application need. Atlas supports transactional, full-text search, vector search, time series and stream processing application use cases across mobile, distributed, event-driven, and serverless architectures.
- Ease of Use
- User Interface
- Scalability
- Features
- Reliability
- Performance
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