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The HDP 3.0 Sandbox provides a pre-configured, single node evaluation environment that you can use with your own data.
HDP 3.0 delivers new capabilities for the enterprise to enable agile application deployment, new machine learning/deep learning workloads, real-time database, & security and governance. It is a key component of the modern data architecture for both on-premises and cloud environments.
- Containerization provides faster time to deployment at a lower TCO
- Supports 3rd party apps in docker containers as well at native YARN containers
- Erasure coding boosts storage efficiency by 50%, allowing efficient data replication to lower total cost of ownership
- Real-time database eliminates the performance gap between low latency and high throughput workloads to process more data at a faster rate
- GPU support accelerates time to insights for more intelligent decisions
- Obtain high performance computing for enterprise machine learning and deep learning apps
- Containerized TensorFlow tech preview combined with GPU pooling for easier designing, building and training for deep learning models
- GPU pooling enables the sharing of GPU resources with more workloads for cost effectiveness
- Automated cloud provisioning to simplify big data deployments while optimizing the use of cloud resources
- Cloud storage support to store endless amounts of data in its native format including ADLS, WASB, S3, GCS (tech preview)
- Cloud agnostic – Cloudbreak provides easy provisioning of clusters in the cloud by deploying HDP to your cloud provider of choice
- Service connectors to cloud including HBase and S3 (tech preview), and Spark with S3Guard for higher query performance
If you are interested in trying the full distribution of the software, please go here.