Cloudera on AWS

What do you like best about the product?

A hybrid data platform approach that enables organizations to manage, govern, and analyze data across on-premises systems, public clouds, and edge environments in a more unified and consistent way. Its main strength is the unified platform for data engineering, analytics, and AI.

What do you dislike about the product?

Cloudera could be complex and expensive, especially for organizations that do not need a full enterprise-scale data platform. Its steeper learning curve, and the need for skilled teams to manage it.

What problems is the product solving and how is that benefiting you?

To help handling large, messy, distributed data that is too expensive or too rigid for traditional data warehouses. It helps organizations store, process, govern, and analyze data across different systems while keeping batch, SQL, search, and real-time workloads in one platform.

What do you like best about the product?

The support team we get with Cloudera is amazing. I mean, they’re great people, and honestly they helped us out a bunch when we were knee-deep in trouble, so I really appreciate the support team.

What do you dislike about the product?

Cloudera upgrades can sometimes be complex because of dependencies between different services, parcels, Java versions, and configuration changes. Planning and validation are important to avoid impacting production workloads.

What problems is the product solving and how is that benefiting you?

Cloudera provides a centralized platform for managing and monitoring Hadoop clusters and services. It helps us manage components like HDFS, YARN, Hive, Kafka, Ranger, and ZooKeeper from a single interface, making cluster administration, monitoring, configuration management, and troubleshooting more efficient. It also helps us maintain cluster stability and identify issues before they significantly impact production workloads.

What do you like best about the product?

What I value most is having access to a stable, up-to-date big data stack that I can run on premises. I also like the flexibility to deploy the platform on premises, in a public cloud, or in a hybrid setup—whatever best fits the environment.

Cloudera data services, in particular, feels like a game changer. It enables users to quickly deploy warehouses, run data engineering jobs, build end-to-end machine learning pipelines, deploy ML models as API/web applications, and roll out LLMs as inference services for enterprise AI. On top of that, Cloudera support has been very helpful and generally responds quickly.

Cloudera is also easy to integrate with our customers existing stack, whether BI tools like Qlik and Tableau, or ETL like Talend and IBM DataStage. It's easy to setup connections from Hive/Impala to Talend for ETL purpose, and then connect them also to Qlik for dashboards.

What do you dislike about the product?

The UI can feel a bit clunky at times and doesn’t come across as very modern. Also, because it’s geared toward stability, integrating some cutting-edge tools with the Cloudera stack can be quite difficult. On top of that, a few of our customers have mentioned that the pricing feels on the higher side compared with competitors.

What problems is the product solving and how is that benefiting you?

We help implement Cloudera for data warehouse migration and modernization, big data initiatives, and Generative AI initiatives. For data warehouse modernization and big data initiatives, our customers benefit from a modern data lakehouse stack, improved performance, and reduced data silos by creating a single source of truth on top of Cloudera. With Cloudera data services, our customers can explore data faster and run ad-hoc reports more easily, powered by Cloudera Data Explorer and Impala on top of virtual warehouses. Cloudera AI also helps our customers get started with their Generative AI use cases, enabling them to quickly create LLM-powered apps without needing to manually set up infrastructure and security.

What do you like best about the product?

Great platform for hosting my tech ecosystem and AI solutions

What do you dislike about the product?

More capabilities on cloud since most of my data is on cloud

What problems is the product solving and how is that benefiting you?

Great platform to host my systems

What do you like best about the product?

one platform served anything essentials in data engineering

What do you dislike about the product?

interface less user friendly, long loading time

What problems is the product solving and how is that benefiting you?

big data processing

What do you like best about the product?

Cloudera is a next-generation platform for data, cloud, and AI solutions that work anywhere.

What do you dislike about the product?

Nothing specific to point out—everything is great.

What problems is the product solving and how is that benefiting you?

Big data platform. It provides a centrally governed foundation for key banking workloads.

What do you like best about the product?

I really appreciate how it provides an all-in-one ecosystem for data engineering and machine learning

What do you dislike about the product?

Setting up and running the ecosystem is notoriously heavy, especially if you are deploying on-premises.

What problems is the product solving and how is that benefiting you?

Cloudera is primarily designed to eliminate the friction, security risks, and high costs associated with managing fragmented, large-scale data ecosystems across multi-cloud and on-premises environments.

What do you like best about the product?

I like that Cloudera allows organizations to leverage modern platforms to run legacy workloads, which helps in getting out of SAS licenses, hardware, and maintenance. I enjoy the idea of 'Cloudera anywhere,' where models can utilize Cloudera data anywhere after migrating from SAS. The initial setup was very easy, which is a big plus for me.

What do you dislike about the product?

I feel like Cloudera is a bit late in the AI and unified data market. Other tech companies had oriented themselves towards these areas a few years earlier than Cloudera did.

What problems is the product solving and how is that benefiting you?

Cloudera allows us to run legacy SAS workloads on a modern platform, helping customers move away from costly SAS licenses, hardware, and maintenance.

What do you like best about the product?

The UI and the features are great, it’s good

What do you dislike about the product?

The ai still has room for improvement, it could be better

What problems is the product solving and how is that benefiting you?

Cloudera provides a unified platform to manage massive enterprise datasets, eliminating data silos across on-premise and cloud environments. It streamlines large-scale data processing pipelines and accelerates our data science workflows by enabling seamless model training and deployment. This has significantly reduced query latency, cut infrastructure management overhead, and empowered our team to deliver faster, data-driven business insights.

What do you like best about the product?

Cloudera stands out for several core capabilities, particularly for enterprises managing complex, large-scale data ecosystems.

Hybrid and multi-cloud flexibility: Cloudera’s “write once, run anywhere” philosophy helps organizations manage workloads smoothly across public clouds, private data centers, and the edge.

Enterprise-grade governance and security: With features like Shared Data Experience (SDX), it offers centralized access control, auditing, and end-to-end data lineage across environments.

Open data lakehouse architecture: Built on open standards like Apache Iceberg, it supports analytics and machine learning directly on large-scale data while avoiding vendor lock-in.

Integrated open-source stack: It combines major big data engines—such as Apache Spark, Kafka, Hive, and NiFi—into a single, managed platform.

What do you dislike about the product?

The AI’s answers sometimes contain mistakes.

What problems is the product solving and how is that benefiting you?

making work simple