Hadoop HDFS
Reviews
Star rating
Rank in Big Data Processing and Distribution
Pros and cons
Pros
- Large Datasets
- Data Storage
- Data Security
- Data Processing
Cons
- Increased Costs
- Maintenance Issues
- Performance Issues
- Security Issues
- Poor Performance
Traffic & LLM citations
Source: G2 review data
Winning from
Losing to
Key stats
Adoption by company size
| Segment | Share of reviews |
|---|---|
| Small Business | 21.4% |
| Mid-Market | 22.9% |
| Enterprise | 55.7% |
Quarterly history
| Quarter | Reviews | Star rating |
|---|---|---|
| 2025 Q3 | 1 | 3.0 |
Satisfaction ratings
What reviewers say
HDFS: Reliable, But Definitely Showing Its Age
“HDFS still does one thing really well store large files across multiple machines with solid fault tolerance. It’s great for batch workloads and works like a charm when paired with Spark, Hive, or traditional Hadoop jobs. Once you’ve set it up right, it’s stable and does its job q”
Compatibility for large/high volume
“It helps in managing large amount very easily.as someone who uses Mssql server exploring and working with Hadoop Hdfs was very good and it gives a new exploration to your knowledge so very good and efficient overall.”
My experience with Hadoop
“The most that I like about hadoop is that it is extremely easy to use and implement. I work with big data and storing that is most convenient with hadoop. Transforming and modelling data is easy with hadoop. The scalability feature of it helps me store large amount of data quickl”