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Cloudera Data Engineering description
Cloudera Data Engineering is a cloud-based tool designed for data teams in large organizations. It helps you build, automate, and manage the process of turning raw data into usable information for analysis or machine learning. It offers a set of tools for visually designing data pipelines, tracking data flow, and ensuring data quality, while integrating with other Cloudera products for data storage and analysis. It aims to make data processing faster, more efficient, and more reliable for businesses that handle large volumes of data.
Who is Cloudera Data Engineering best for
Cloudera Data Engineering is a robust cloud platform for building, automating, and managing data pipelines. Designed for large enterprises with complex data needs, it offers a visual interface for designing workflows, tracking data flow, and ensuring data quality. While praised for its robust security and scalability, some users note a steep learning curve and high cost.
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Ideal for large enterprises (1000+ employees) with dedicated data engineering teams.
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Best fit for software, IT, and telecommunications companies.
Cloudera Data Engineering features
Supported Provides a visual interface for designing and managing data pipelines, simplifying complex workflows. |
Supported Enables users to track the flow of data through the pipelines and understand data lineage. |
Supported Includes tools to ensure data quality throughout the data lifecycle. |
Supported Seamless integration with other Cloudera products, such as Data Warehouse and Machine Learning. |
Supported Provides automation capabilities for data pipelines, improving efficiency and reducing manual effort. |
Supported Includes tools for monitoring pipeline performance, identifying bottlenecks, and troubleshooting issues. |
Supported Offers visual tools for troubleshooting data pipeline issues. |
Cloudera Data Engineering reviews
We've summarised 22 Cloudera Data Engineering reviews (Cloudera Data Engineering G2 reviews) and summarised the main points below.
- Robust security features for enterprise-level data engineering.
- User-friendly interface and easy integration with other tools.
- Excellent customer support.
- Built on Apache Spark and Airflow for efficient automation and monitoring.
- Scalable for large data volumes.
- High cost, especially for large data volumes.
- Limited data science and visualization interface.
- Slow UI.
- Difficult API integrations.
- Steep learning curve, requires supervision initially.
Cloudera Data Engineering pricing
The commentary is based on 6 reviews from Cloudera Data Engineering G2 reviews.
Cloudera Data Engineering offers robust data processing capabilities but reviews indicate it can be expensive, especially for large datasets. While some appreciate its pay-as-you-go model, the enterprise pricing structure is a concern for others. Cost-conscious users should carefully evaluate their needs and budget.
See the Cloudera Data Engineering pricing page.
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Cloudera Data Engineering has a free trial.
Develop, schedule, monitor, and debug data pipelines to streamline ETL processes quickly & securely.
Develop, schedule, monitor, and debug data pipelines to streamline ETL processes quickly & securely.
Deploy data warehouses with secure, self-service access to enterprise data.
Develop future-proof applications that deliver unparalleled scale, performance, and reliability.
Provide collaborative ML workspaces with secure, self-service access to enterprise data.
Easily manage clusters running Apache Spark, Hive, Impala, HBase, Phoenix, Kafka, Flink, and more.
A premium Data Hub service to ingest, transform and manage streaming data, powered by Apache NiFi.
Catalog, deploy, manage and monitor Apache NiFi data flow deployments and functions.
Catalog, deploy, manage and monitor Apache NiFi data flow deployments and functions.
Monitor and optimize CDP deployments across hybrid cloud.
Utilize private connections between CDP deployments and the CDP Control Plane
Deploying and managing traditional models, large language models (LLMs), and generative AI models with high performance, security, and scalability
Easy to use, auto-scaling Data Engineering, Data Warehouse, and Machine Learning Data Services that rely on CDP Private Cloud Base for HDFS, Ozone object storage, or select third party storage, with SDX technologies.
Modernized data clusters built with modern open-source data management and analytics software. Powered by the Apache Iceberg open table format to handle large analytic datasets with reliability while built-in automations guarantee improved performance and productivity. Run against HDFS files stores, high-density Ozone object storage, or select third party storage, with SDX technologies.
Cloudera Data Engineering alternatives
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Cloudera Data Engineering FAQ
Cloudera Data Engineering (CDE) is a cloud-based data engineering platform for building, automating, and managing data pipelines. CDE offers a visual interface for designing workflows, tracking data flow, ensuring data quality, and integrating with other Cloudera products. It simplifies complex data processing for large organizations, enhancing speed, efficiency, and reliability.
What is Cloudera Data Engineering and what does Cloudera Data Engineering do?
Cloudera Data Engineering (CDE) is a cloud-based data engineering platform for building, automating, and managing data pipelines. CDE offers a visual interface for designing workflows, tracking data flow, ensuring data quality, and integrating with other Cloudera products. It simplifies complex data processing for large organizations, enhancing speed, efficiency, and reliability.
Cloudera Data Engineering integrates seamlessly with other Cloudera data platform products, such as Cloudera Data Warehouse and Cloudera Machine Learning, simplifying data workflows. It also supports integrations via APIs. However, some users find the API integrations challenging.
How does Cloudera Data Engineering integrate with other tools?
Cloudera Data Engineering integrates seamlessly with other Cloudera data platform products, such as Cloudera Data Warehouse and Cloudera Machine Learning, simplifying data workflows. It also supports integrations via APIs. However, some users find the API integrations challenging.
Top competitors to Cloudera Data Engineering include Montara, a collaborative data platform for infrastructure management, and SAS Visual Data Mining and Machine Learning, offering robust data analysis and predictive modeling capabilities. Other alternatives include Qlik AutoML for automated machine learning, and TensorFlow for building and managing ML applications.
What the main competitors of Cloudera Data Engineering?
Top competitors to Cloudera Data Engineering include Montara, a collaborative data platform for infrastructure management, and SAS Visual Data Mining and Machine Learning, offering robust data analysis and predictive modeling capabilities. Other alternatives include Qlik AutoML for automated machine learning, and TensorFlow for building and managing ML applications.
Cloudera Data Engineering is a legitimate cloud-based data engineering tool. It's known for robust security and a user-friendly interface but can be costly. It's ideal for large enterprises with complex data pipelines needing a scalable and secure platform.
Is Cloudera Data Engineering legit?
Cloudera Data Engineering is a legitimate cloud-based data engineering tool. It's known for robust security and a user-friendly interface but can be costly. It's ideal for large enterprises with complex data pipelines needing a scalable and secure platform.
Cloudera Data Engineering offers various services priced per Cloudera Compute Unit (CCU). Prices range from $0.07 for Core and Data Warehouse services to $0.30 for Deployments & Test Sessions. Data Services are priced at $650, while the Base service is $10,000. Several add-ons further expand data engineering product pricing.
How much does Cloudera Data Engineering cost?
Cloudera Data Engineering offers various services priced per Cloudera Compute Unit (CCU). Prices range from $0.07 for Core and Data Warehouse services to $0.30 for Deployments & Test Sessions. Data Services are priced at $650, while the Base service is $10,000. Several add-ons further expand data engineering product pricing.
Cloudera Data Engineering's customer service receives positive feedback. Users highlight the excellent and helpful support team, quick responses to problems, and readily available assistance throughout the platform. However, documentation and community support are considered limited.
Is Cloudera Data Engineering customer service good?
Cloudera Data Engineering's customer service receives positive feedback. Users highlight the excellent and helpful support team, quick responses to problems, and readily available assistance throughout the platform. However, documentation and community support are considered limited.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.
An AI tool that observes your work, finds inefficiencies, and suggests smarter ways to do things. Maybe you can use your tools better, automate tasks, or switch software.