Altiscale and Cloudera Data Platform are key players in the big data solutions arena. Cloudera Data Platform is regarded as more robust, providing additional features and scalability, making it preferable for enterprises needing extensive data capabilities.
Features: Altiscale is recognized for its cloud-based big data processing, offering streamlined deployment, and is particularly beneficial for quick implementations. Cloudera Data Platform provides advanced analytics, machine learning capabilities, and comprehensive data management tools, appealing to businesses with more extensive data solution needs.
Ease of Deployment and Customer Service: Altiscale is known for rapid deployment and simplicity, reducing time to market. Cloudera Data Platform, although more complex to set up, offers robust customer support aiding in detailed configuration and scalability.
Pricing and ROI: Altiscale presents lower initial costs and quicker returns due to its cloud-first approach, suitable for smaller enterprises. Cloudera Data Platform, despite higher upfront expenses, ensures significant long-term advantages, ideal for organizations requiring sophisticated data processing.
Liberate your data, by making it possible for any data analyst in your company to access and rapidly analyze data in the Hadoop data lake, without burdening your IT team. The Altiscale Insight Cloud handles both real-time and batch analytics, and connects easily to your favorite BI solutions.
Cloudera Data Platform offers a powerful fusion of Hadoop technology and user-centric tools, enabling seamless scalability and open-source flexibility. It supports large-scale data operations with tools like Ranger and Cloudera Data Science Workbench, offering efficient cluster management and containerization capabilities.
Designed to support extensive data needs, Cloudera Data Platform encompasses a comprehensive Hadoop stack, which includes HDFS, Hive, and Spark. Its integration with Ambari provides user-friendliness in management and configuration. Despite its strengths in scalability and security, Cloudera Data Platform requires enhancements in multi-tenant implementation, governance, and UI, while attribute-level encryption and better HDFS namenode support are also needed. Stability, especially regarding the Hue UI, financial costs, and disaster recovery are notable challenges. Additionally, integration with cloud storage and deployment methods could be more intuitive to enhance user experience, along with more effective support and community engagement.
What are the key features?Cloudera Data Platform is implemented extensively across industries like hospitality for data science activities, including managing historical data. Its adaptability extends to operational analytics for sectors like oil & gas, finance, and healthcare, often enhanced by Hortonworks Data Platform for data ingestion and analytics tasks.
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