Hadoop HDFS vs. Microsoft SQL Server
A side-by-side comparison based on G2 review data.
| Metric | Hadoop HDFS | Microsoft SQL Server |
|---|---|---|
| Overall rating | 4.4 | 4.4 |
| Review count | 141 | 2,289 |
| Ease of use | 7.9 | 8.8 |
| Ease of setup | 7.4 | 8.4 |
| Quality of support | 8.1 | 8.6 |
| Meets requirements | 8.8 | 9.2 |
| NPS | 54.615385 | 57.082552 |
| Small Business | 21.4% | 18.7% |
| Mid-Market | 22.9% | 36.3% |
| Enterprise | 55.7% | 45.0% |
| Total page views | 100 | 1,482 |
| Total LLM citations | 201 | 2,771 |
Hadoop HDFS
The Hadoop Distributed File System (HDFS) is a scalable and fault-tolerant file system designed to manage large datasets across clusters of commodity hardware. As a core component of the Apache Hadoop ecosystem, HDFS enables efficient storage and retrieval of vast amounts of data, making it ideal for big data applications. Key Features and Functionality: - Fault Tolerance: HDFS replicates data blocks across multiple nodes, ensuring data availability and resilience against hardware failures.
- Large Datasets
- Data Storage
- Data Security
- Data Processing
Microsoft SQL Server
SQL Server 2017 brings the power of SQL Server to Windows, Linux and Docker containers for the first time ever, enabling developers to build intelligent applications using their preferred language and environment. Experience industry-leading performance, rest assured with innovative security features, transform your business with AI built-in, and deliver insights wherever your users are with mobile BI.
- Ease of Use
- Database Management
- Performance
- Easy Integrations
- Features
- Integrations