Spark SQL vs. Amazon Aurora
A side-by-side comparison based on G2 review data.
| Metric | Spark SQL | Amazon Aurora |
|---|---|---|
| Overall rating | 4.6 | 4.5 |
| Review count | 46 | 456 |
| Ease of use | 9.1 | 8.9 |
| Ease of setup | 9.0 | 8.8 |
| Quality of support | 8.6 | 8.9 |
| Meets requirements | 9.0 | 9.1 |
| NPS | 69.565217 | 65.517241 |
| Small Business | 26.1% | 37.7% |
| Mid-Market | 19.6% | 33.8% |
| Enterprise | 54.3% | 28.5% |
| Total page views | 35 | 391 |
| Total LLM citations | 20 | 1,532 |
Spark SQL
Spark SQL lets you query structured data inside Spark programs, using either SQL or a familiar DataFrame API. Usable in Java, Scala, Python and R.
Amazon Aurora
Amazon Aurora is a fully managed relational database service that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. Compatible with MySQL and PostgreSQL, Aurora delivers up to five times the throughput of standard MySQL databases and up to three times that of standard PostgreSQL databases. It is designed for high availability, offering up to 99.99% availability within a single region and up to 99.999% across multiple regions.
- Scalability
- Ease of Use
- Availability
- Performance
- Reliability
- High Availability