| Product | Market Share (%) |
|---|---|
| Cloudera Distribution for Hadoop | 23.3% |
| Apache Spark | 19.2% |
| HPE Ezmeral Data Fabric | 14.8% |
| Other | 42.7% |
| Type | Title | Date | |
|---|---|---|---|
| Category | Hadoop | Aug 29, 2025 | Download |
| Product | Reviews, tips, and advice from real users | Aug 29, 2025 | Download |
| Comparison | Cloudera Distribution for Hadoop vs Apache Spark | Aug 29, 2025 | Download |
| Comparison | Cloudera Distribution for Hadoop vs Amazon EMR | Aug 29, 2025 | Download |
| Comparison | Cloudera Distribution for Hadoop vs HPE Ezmeral Data Fabric | Aug 29, 2025 | Download |
| Title | Rating | Mindshare | Recommending | |
|---|---|---|---|---|
| MongoDB Enterprise Advanced | 4.1 | N/A | 92% | 81 interviewsAdd to research |
| Apache Spark | 4.2 | 19.2% | 90% | 67 interviewsAdd to research |
| Company Size | Count |
|---|---|
| Small Business | 15 |
| Midsize Enterprise | 7 |
| Large Enterprise | 22 |
| Company Size | Count |
|---|---|
| Small Business | 60 |
| Midsize Enterprise | 32 |
| Large Enterprise | 224 |
| Author info | Rating | Review Summary |
|---|---|---|
| Manager, Bussines Development & Co Owner at Troia d.o.o. | 4.5 | I implemented Cloudera Distribution for Hadoop for an electrical distribution company to collect data from smart meters. It's unique for on-premises installation and offers a powerful hybrid solution. However, it's complex to configure, especially with Active Directory integration. |
| Head of Advaced Analytics & Intelligence; AGM at Alinma Bank | 4.0 | I've used Cloudera Distribution for Hadoop for several years for analytics and large-scale data processing. It's stable, scalable, secure, and effective, though data modification could be easier. Overall, the experience and ROI have been positive. |
| Senior IT Application Architect at a insurance company with 5,001-10,000 employees | 3.5 | We use Cloudera Distribution for Hadoop primarily for computing with Spark, Hive, HDFS, and Impala. Its secure environment meets our protection needs, but competitors offer better functionalities. We considered Databricks for its effective cloud capabilities. |
| Senior Data Architect at Teradata Corporation | 4.0 | I use Cloudera Distribution for Hadoop for workflow distribution and real-time processing. Its distributed file system and unstructured data processing are valuable, but it lacks reporting support, relying on relational databases. Improvements in machine learning are needed. |
| Senior Business Development Manager at BBI Consultancy | 4.5 | In our experience, Cloudera is ideal for on-premises big data management, offering excellent scalability through container technologies. However, its cloud deployment capabilities require improvement, as competitors currently surpass Cloudera in this area for cloud-based solutions. |
| Senior Architect at a comms service provider with 1,001-5,000 employees | 4.0 | In my experience with Cloudera Distribution for Hadoop, managing data services centrally is beneficial, but its outdated nature led us to switch to Airflow. Cloudera lacks containerization, which complicates deployment upgrades compared to a Kubernetes-based approach. |
| BI Manager at Discovery Health | 4.0 | We use Cloudera Distribution for Hadoop primarily for machine learning, valuing its data science capabilities. However, we find the governance aspect needs improvement, and the pricing renewal notices can be challenging. We've previously worked with Hortonworks. |
| Head of Big Data and Analytics Competency center at OTP Bank Hungary | 4.0 | No summary available |
