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    Cloudera on AWS

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    Sold by: Cloudera 
    Deployed on AWS
    An enterprise data cloud that manages, secures and connects the data lifecycle in AWS. Cloudera delivers powerful self-service analytics across hybrid and multi-cloud environments, along with sophisticated and granular security and governance policies that IT and data leaders demand.

    Overview

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    Cloudera on AWS is an enterprise data platform that is easy to deploy, manage, and use. By simplifying operations, Cloudera reduces the time to onboard new use cases. Cloudera manages data in any environment, including multiple public clouds, private cloud, and hybrid cloud. With Cloudera's Shared Data Experience (SDX), IT can confidently deliver secure and governed analytics running against data anywhere. Cloudera is a new approach to enterprise data, running anywhere from the Edge to AI.

    Cloudera on AWS delivers easy-to-use analytics that support the most complex, demanding use cases

    Complete: All functions needed to ingest, transform, query, optimize, and make predictions from data are available, eliminating the need for point products

    Integrated: Unified analytic functions work together eliminating data silos and copies of data

    Cloudera SDX technologies ensures and enterprise data cloud is secure by design:

    Consistency: Security and governance policies are set once and applied across all data and workloads

    Portability: Policies stay with the data even as it moves across all supported infrastructures

    Pricing: Use of Cloudera on AWS requires a prepay commitment (in dollars) of cloud credits. For more information on usage rates and instance types, see cloudera.com/products/pricing.html.

    You may use the platform until your commitment is consumed (used against prepaid commitment amount), any additional usage beyond the prepaid commitment will require negotiation with Cloudera for the purchase of additional prepaid credits.

    Highlights

    • Provides elasticity, agility, and ease of use for hybrid and public cloud by intelligently autoscaling workloads up and down for more cost-effective use of cloud infrastructure. Consistent user experience makes it faster and easier to analyze data.
    • Optimizes the data lifecycle with multi-function analytics that solves demanding business use cases. Cloudera on AWS is composed of three primary services with a standardized user experience: Data Warehouse, Machine Learning and Data Hub for custom analytics.
    • Ensures all workloads on the platform share common security, governance, and metadata. Users can efficiently find, curate, and share data, enabling self-service access to trusted data and analytics

    Details

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    Deployed on AWS

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    Pricing

    Cloudera on AWS

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    Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    12-month contract (1)

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    Description
    Cost/12 months
    Cloudera
    Subscription Cloudera on AWS
    $50,000.00

    Additional usage costs (1)

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    The following dimensions are not included in the contract terms, which will be charged based on your usage.

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    Cost/unit
    Consumption by Customer based on Cloud usage
    $0.01

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    Delivery details

    Software as a Service (SaaS)

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    Product comparison

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    Accolades

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    Top
    10
    In Data Analysis
    Top
    10
    In Databases & Analytics Platforms, ML Solutions, Data Analytics
    Top
    10
    In Data Warehouses

    Customer reviews

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    Sentiment is AI generated from actual customer reviews on AWS and G2
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    Overview

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    AI generated from product descriptions
    Data Platform Architecture
    Enterprise data platform supporting multi-cloud, hybrid cloud, and on-premises data management environments
    Security and Governance Framework
    Shared Data Experience (SDX) technology providing consistent security and governance policies across data workloads and infrastructures
    Multi-Function Analytics
    Integrated analytics platform supporting data ingestion, transformation, querying, optimization, and predictive modeling without requiring separate point products
    Workload Optimization
    Intelligent autoscaling capabilities for dynamically adjusting cloud infrastructure resources based on computational requirements
    Data Lifecycle Management
    Comprehensive platform supporting data processing across multiple services including Data Warehouse, Machine Learning, and custom analytics environments
    Data Platform Architecture
    Unified platform integrating data engineering, analytics, business intelligence, data science, and machine learning on a single architecture
    Open Source Foundation
    Built on open source data projects with support for open standards and data formats
    Lakehouse Infrastructure
    Provides a common data management approach using a lakehouse architecture running on Amazon S3
    Data Intelligence Engine
    Advanced engine capable of interpreting organizational data context and enabling broad data access across teams
    Collaborative Workflow
    Native collaboration capabilities enabling cross-functional data and AI workflow integration
    Data Lake Query Performance
    Provides sub-second query response times using SQL query service on data lake platforms
    Open Standards Support
    Utilizes community-driven standards like Apache Iceberg and Apache Arrow for processing engines
    Multi-Source Data Integration
    Enables joining data from data lakes and external databases without data movement
    Compute Engine Management
    Automatically handles compute engine lifecycle including provisioning, scaling, pausing, and decommissioning
    VPC-Based Data Processing
    Deploys compute engines within customer's Amazon Virtual Private Cloud for secure data processing

    Security credentials

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    Validated by AWS Marketplace
    FedRAMP
    GDPR
    HIPAA
    ISO/IEC 27001
    PCI DSS
    SOC 2 Type 2
    No security profile
    No security profile
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    Contract

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    Standard contract
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    Customer reviews

    Ratings and reviews

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    2
    2 ratings
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    4 star
    3 star
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    2 AWS reviews
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    46 external reviews
    Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
    reviewer2776239

    Uses handwritten notes and voice files to perform text analytics and gain real-time insights

    Reviewed on Nov 12, 2025
    Review provided by PeerSpot

    What is our primary use case?

    My main use case for Cloudera Data Platform  is dealing with large volumes of data and primarily handling unstructured data by combining structured and unstructured data on this platform.

    I use Cloudera Data Platform  for handling unstructured data primarily in a healthcare company where there are many research notes, which are handwritten notes. Using this platform, we have performed PDF extraction where we store PDF data and then extract the data by performing PDF extraction using this platform. That is one use case. The second use case is mainly dealing with voice files. We store the voice files, convert voice to text, and then perform text analytics on that. It is basically dealing with call center voice files.

    How has it helped my organization?

    Cloudera Data Platform has impacted my organization positively in many ways. I belong to the service industry, and many of my customers are using this platform. They are predominantly using Cloudera Data Platform mainly from the banking domain.

    It has made things better for those banking customers by providing all of the above.

    What is most valuable?

    The best features Cloudera Data Platform offers are from the earlier version, and if you see the latest version, there is significant change. It is very much end-user friendly. There are many user interfaces that they have added. A single pane for administration is easy from a data engineering perspective. You can use drag and drop more in the UI features; they are providing good dashboards to understand the performance of your platform. Ready metrics are available. It is very easy administration from a data platform standpoint. There are many other areas such as data principles including lineage and data security, all of which are really coming out of the box of this platform.

    The dashboards and drag-and-drop tools have helped my team because the metrics are already available. As an administrator of the platform, certain key metrics are already available as a dropdown. You can select and pick whichever you want, and based on that, you will be able to see memory utilization and disk utilization. Based on that, you can make a decision such as whether you need to do some performance tweaks or add more hardware to your clusters. Those sorts of insights and early alerts help you to do that. That is also another feature available within the platform. From the administration perspective, it is really helpful for the data administrator or a platform administrator.

    What needs improvement?

    Cloudera Data Platform can be improved in several areas. I recently attended their roadmap session. Whatever limitations they have identified involve moving data from on-premises to cloud as a single-pane view and better lineage. They have done some recent acquisitions as well to overcome their product limitations. They are on the right track by doing this analysis themselves, identifying what the weaknesses are, and then using mergers or acquisitions to overcome them.

    I would like to add that, beyond the platform itself, they should provide more training to systems integrators so that they can have a more ready workforce to use Cloudera Data Platform.

    For how long have I used the solution?

    I have been using Cloudera Data Platform for almost ten years.

    What do I think about the stability of the solution?

    Cloudera Data Platform is pretty stable in my experience; there are not any downtime or reliability issues.

    In large environments or with growing data needs, I have seen hundred-node clusters running fine, dealing with petabytes of data. I have not seen any issues. When we go for node addition or node rebalancing, there are sometimes issues usually dealt with. It is not a major issue per se; it is more about how you deal with that particular situation.

    What do I think about the scalability of the solution?

    I manage scalability with Cloudera Data Platform, and the current features available are better now. They have the cloud burst feature available where if the on-premises capacity is not sufficient at a point in time, you can run that Spark job on the cloud itself. The cloud burst feature which they have recently added allows better scalability from a perspective to utilize a better ecosystem provider as well.

    How are customer service and support?

    My experience with customer support for Cloudera Data Platform is good. I have not majorly dealt with them, but whatever I have heard from my various team members indicates that customer support is good. They provide good pre-sale support and overall handholding to identify the right use case and technologies. Overall, they provide good support from the company.

    Customer support is responsive and knowledgeable, but since I have not actually dealt with them extensively, I will not be able to provide a scale on one to ten.

    How would you rate customer service and support?

    Neutral

    Which solution did I use previously and why did I switch?

    I did not use a different solution before Cloudera Data Platform; we used to use only structured databases for our data warehousing solution. It is a move from only structured data or on-premises appliance-based solutions to Cloudera Data Platform.

    What was our ROI?

    I have seen a return on investment. There are licensing costs that have been saved when we moved some of the data platforms, decommissioned them, and moved on to this platform. Time has been saved by implementing the right data quality solution so that the team used to spend more time correcting data. The right data quality solution saves time. It helps the time usually spent by business analysts who go to search in Excel to understand data definitions. Now that is something easily available as a part of the data catalog. Such things usually save license cost and money, as the time which business analysts are spending to get more information about the data dictionary is saved as part of the data catalog.

    What's my experience with pricing, setup cost, and licensing?

    My experience with pricing, setup cost, and licensing varies based on your relationship and the size of the cluster. So far, I would say that it is competitive pricing that we have received.

    Which other solutions did I evaluate?

    Before choosing Cloudera Data Platform, I did evaluate other options. Earlier, it was Cloudera, Hortonworks, and MapR , but nowadays, with Hortonworks and Cloudera merging, it is predominantly Cloudera Data Platform for big data on-premises.

    What other advice do I have?

    My advice for others looking into using Cloudera Data Platform is to consider the fact that it has been around for more than a decade, making it a very stable solution. If you want to go with the on-premises solution, that is the way you should go. If you are looking for a solution to deal with large volume, variety of data, and velocity of data including real-time data processing, that is something you should select with this platform. Based on the industry, there are various use cases available in their use case manual where particular use cases are more suitable for the customer's industry; they can also help you select the right services or the right product stack from Cloudera. It is all good, and you should leverage their professional services to get a better and more suitable product architecture. I would rate this product an eight out of ten.

    reviewer2774499

    Has improved data analysis workflows and centralized sensitive information but needs faster adoption of latest technologies

    Reviewed on Nov 04, 2025
    Review provided by PeerSpot

    What is our primary use case?

    My main use case for Cloudera Data Platform  is to host in-house data which is sensitive and very guard-railed for compliance.

    A quick specific example of the type of sensitive data I'm hosting is related to personally identifiable information as well as data which is financial and transactional in nature, and Cloudera Data Platform  helps with compliance by giving us a uniform approach to this. We have implemented the compliance-based entitlements using toolkits provided by Cloudera Data Platform and have our own implementation for each region where we are hosting the data.

    What is most valuable?

    The most unique thing about my setup with Cloudera Data Platform is having loads and loads of high-volume data, even for specific geographies, and using Cloudera Data Platform has helped us modernize that in a way where the tech is simpler for us.

    The best features Cloudera Data Platform offers include their Kafka and Spark offerings, which we are using majorly, along with the Sqoop offering and a bit of Airflow  here and there. The standout offering we have used from them is the Spark engine and the Impala engine to query our data, making the Impala cluster the best thing we have used from them.

    Using the Spark and Impala engines makes my daily work easier and more efficient because Impala gives us a way to easily do analysis on the data, which simplifies the work of a business analyst as well as a PM when they are doing the initial analysis before the actual development begins for Spark, helping reduce the overall development cycle time.

    Cloudera Data Platform has impacted my organization positively by providing cost-saving benefits, which is the North Star because of which we have shifted to it. We had data distributed across many platforms before starting this, and now the entire data strategy is designed around Cloudera Data Platform because it is very simple and very configurable.

    What needs improvement?

    A major drawback that I see with Cloudera Data Platform is that it tends to be one or two years behind the latest open-source implementation of the Apache toolkits such as Spark, Hive , and everything else, which relates to the guardrails of following compliance as the main driving factor, so that is something that could be done better on Cloudera Data Platform's side.

    For how long have I used the solution?

    I have been using Cloudera Data Platform for the last five years.

    What do I think about the stability of the solution?

    Cloudera Data Platform is stable most of the time.

    What do I think about the scalability of the solution?

    The scalability of Cloudera Data Platform is the best part about it, as you can just add, and the horizontal scaling is very fast, while vertical scaling takes a bit of time, but that works as well.

    How are customer service and support?

    The customer support for Cloudera Data Platform is okay; I would not say they are the best with technical abilities, however, they are able to address most of the issues.

    How would you rate customer service and support?

    Neutral

    Which solution did I use previously and why did I switch?

    Before choosing Cloudera Data Platform, we were using an IBM Netezza  solution, which was working for the last ten years, but the costing was getting pretty high as we were scaling.

    What was our ROI?

    The major improvement we have is the consolidation of all the data models that we had, as now we have everything designed for Cloudera Data Platform, which saves a lot of time when we are doing exchanges between various teams.

    Which other solutions did I evaluate?

    I was not part of the exercise to evaluate other options before choosing Cloudera Data Platform, so I cannot comment on that.

    What other advice do I have?

    I would like to add that we are using Kafka in some cases across geographies as well, if the compliances allow us, and it has helped us maintain data pipelines more easily.

    While I do not have exact numbers, I can tell you that we are processing more than a million data points every day on Cloudera Data Platform.

    I don't have anything else to add about needed improvements regarding support, documentation, or other features.

    My advice for others looking into using Cloudera Data Platform is to start with using the cloud and see if you can stay on the cloud if your domain allows, because being on the cloud gives you faster adoption to new technologies as well as distributed technical implementation, which provides more stability and flexibility.

    I would rate this product a seven out of ten.

    Sajid Mehmood

    Have managed data services efficiently while ensuring fast performance and reliability

    Reviewed on Oct 30, 2025
    Review provided by PeerSpot

    What is our primary use case?

    My main use case for Cloudera Data Platform  is that I am a certified administrator. I use Cloudera Data Platform  in my daily work by managing it as a whole in a Telco company. I regularly handle tasks by managing Cloudera Data Platform and being responsible for its services, which are currently up and running, and managing daily administrative tasks.

    What is most valuable?

    In my experience, the best features Cloudera Data Platform offers are that all the services provided are excellent.

    A particular service that stands out to me in Cloudera Data Platform is the performance, which runs very fast. I also find very good features in data security, data reliability, and data lineage.

    Cloudera Data Platform's Manager UI and other UIs are very useful and helpful for managing operations.

    Cloudera Data Platform has positively impacted my organization as it comes in very handy while performing on big data and handling large files.

    What needs improvement?

    I think Cloudera Data Platform is good enough to run now, and I do not see areas for significant improvement.

    I wish Cloudera Data Platform would add a service, apart from Ozone , to handle small files with faster performance, so as not to use Ozone  or add extra hard disk capacity to the cluster.

    For how long have I used the solution?

    I have been using Cloudera Data Platform for approximately five years.

    What do I think about the stability of the solution?

    Cloudera Data Platform is very stable in my experience.

    What do I think about the scalability of the solution?

    Scalability of Cloudera Data Platform is very good and scalable in public cloud. However, it is not as scalable on on-premises private cloud, which adds considerable cost.

    How are customer service and support?

    I have interacted with the customer support team extensively, and they are very useful and helpful in resolving issues. I would rate the customer support of Cloudera Data Platform ten out of ten.

    How would you rate customer service and support?

    Positive

    Which solution did I use previously and why did I switch?

    Before choosing Cloudera Data Platform, my organization was using Teradata , and we did not evaluate other options.

    Review4321

    Has supported multi-source data integration and enabled real-time analytics across hybrid environments

    Reviewed on Oct 27, 2025
    Review from a verified AWS customer

    What is our primary use case?

    The main use case for Cloudera Data Platform is to support a multi-source system with a multi-data structure. We have streaming services, Kafka services, RDBMS systems, and semi-structured data in the form of CSV and JSON files where we used to have everything in place and centralized.

    Cloudera Data Platform also supports a hybrid data warehouse, which is similar to a relational database management system where business users can do query analytics, similar to a select star. Cloudera Data Platform also supports PySpark, where a user can create a data frame and then do a transformation load to perform and get insights.

    What is most valuable?

    The best features of Cloudera Data Platform are that it supports hybrid types of environments, real-time streaming analytics, secure data and governance, machine learning and AI workloads, data warehousing and BI, and edge-to-edge AI use cases.

    In the hybrid environment, we can have a private cloud as well as a public cloud, which helps us enable both types of workloads. We have data that keeps coming through a pipeline, and then we just ingest our data. The data engineer transforms and loads it to a data lake, which is Amazon S3. Once the data is ready, it's on the downstream, and it's available for the consumer end to consume the data.

    The most important features of Cloudera Data Platform are Rangers, which provide a granular level of security, allowing you to provide column-level security and decide what column you want to expose to the consumer, not just the tabular level.

    Cloudera Data Platform has a great impact on my organization as it supports the business demand and business requirements, making me happy with the business use case. It depends on what the business demands and the business use case, which allows for an evaluation of what the business wants. Based on that, they can make a decision on where to go and where to migrate a workload.

    What needs improvement?

    I would definitely want to see more on the invention part of Cloudera Data Platform to provide a full-fledged AI and ML workload, as AI is supported currently, but I'm interested in having ML and LLM also supported in a full-fledged manner.

    For how long have I used the solution?

    I have been working in the current field for almost six to eight years.

    What do I think about the stability of the solution?

    Cloudera Data Platform is stable.

    What do I think about the scalability of the solution?

    Cloudera Data Platform's scalability is very nice, as you can have multiple workloads and even have multiple clusters with different CDP runtimes. You just have to define the business requirement in the configuration, and based on usage, it automatically scales up and scales down.

    How are customer service and support?

    Customer support for Cloudera Data Platform is very good.

    How would you rate customer service and support?

    Positive

    Which solution did I use previously and why did I switch?

    We have been using a Cloudera distribution for Hadoop, which is a CDP product, a CDH product. The CDH product provided on-premises only, so we migrated from on-premises to the cloud to opt for cloud compute.

    How was the initial setup?

    The experience with pricing, setup cost, and licensing is very good. The cloud service provider has an inbuilt tool to analyze what zone and what region to use, as the services have costs associated with that, allowing us to manipulate which region is best suitable and cheaper.

    What was our ROI?

    In terms of ROI, we definitely have seen a return on investment. Due to security, we cannot disclose the value, but we have definitely seen an ROI.

    What's my experience with pricing, setup cost, and licensing?

    The experience with pricing, setup cost, and licensing is very good.

    Which other solutions did I evaluate?

    I did not evaluate other options before choosing Cloudera Data Platform.

    What other advice do I have?

    I would rate Cloudera Data Platform an eight out of ten because it's excellent in terms of the product, its deliverability, its support, and its use cases. It might differ for different industries depending on what each industry wants, but overall, it has a good impression, and I'm happy with the work relationship with Cloudera technical support.

    If someone is looking for a hybrid environment or a cloud environment, they can definitely consider reviewing Cloudera Data Platform. They can look at all the aspects, as the Cloudera Data Platform ecosystem provides Apache Hive, HBase, Kafka, NiFi, Solr, and Knox, which they can review based on their business use case.

    Which deployment model are you using for this solution?

    Public Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Amazon Web Services (AWS)
    T Sarwar

    Has enabled efficient big data processing and querying but remains complex to manage and configure

    Reviewed on Oct 24, 2025
    Review provided by PeerSpot

    What is our primary use case?

    We are using Cloudera Data Platform  to migrate and run our ETL processes, transferring data from multiple RDBMS  to a data lake for analysis purposes. The current organization I work for is a top bank with a data lake of more than one petabyte.

    Cloudera Data Platform  is a perfect tool to manage such vast amounts of big data, store it properly, query it, and move it from one end to another.

    What is most valuable?

    The most useful feature I currently use from Cloudera Data Platform is the Hue tool, which provides a web-based utility. Users don't need network access approval when using on-premises internal access. Additionally, Spark and Impala are the most useful tools that I have used from Cloudera Data Platform.

    The current organization I work for is a top bank with a data lake of more than one petabyte. For this specific purpose, Cloudera Data Platform is a perfect tool to manage such vast amounts of big data, store it properly, query it, and move it from one end to another.

    What needs improvement?

    Cloudera Data Platform should use fewer tools and remove the complexity between them. It should make it easier for the end user to change the configuration and understand it better.

    The UI tool for jobs in Cloudera Data Platform can be improved to provide a proper image of ETL jobs and detailed consolidated graphs to monitor Spark-based Hue jobs.

    For how long have I used the solution?

    I have been working on a big data platform for the last five years, starting from 2020. Initially, I worked on Hortonworks platform for the last two to three years. Since Cloudera and Hortonworks merged into a single platform which is Cloudera Data Platform, I have been working on the CDP platform for the last two years.

    What do I think about the stability of the solution?

    We face downtime and reliability issues many times a week with Cloudera Data Platform because it is a very complex system and all configurations are managed by the end user. Sometimes the end user is not experienced or does not have all the expertise related to Cloudera specifically, making it very difficult to manage properly.

    What do I think about the scalability of the solution?

    For scalability, I would rate Cloudera Data Platform nine out of 10. We periodically have requirements to add resources or servers, and we find it very useful from a scalability perspective.

    How are customer service and support?

    The customer support from Cloudera is good when we receive support from non-Indian representatives. When support comes from Indian representatives, we receive level one support only.

    How would you rate customer service and support?

    Neutral

    Which solution did I use previously and why did I switch?

    Previously we were using Hive  tool for querying engine, but since installing Impala, we witnessed huge performance improvements with Cloudera Data Platform. The majority of users are using Impala instead of Hive  because Impala uses MPP, massively parallel processing technology.

    Which other solutions did I evaluate?

    If the only requirement is to have an on-premises system without other options, then Cloudera Data Platform is the best option available. However, if cloud is an option, I would prefer cloud more than on-premises Cloudera system.

    What other advice do I have?

    We are currently using Cloudera Data Platform with specific tools: Rangers to manage access-related items, HDFS to store files, Hive and Impala to access them, Hue as a query editor, and Spark for ETL execution.

    It is a very complex system compared to cloud technology, which is much simpler. Due to this complexity, I rate Cloudera Data Platform six out of 10.

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