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Greenplum is designed to run anywhere—on-premises, in public and private clouds, and in modern containerized environments like Kubernetes—for easier installation, operation, and upgrades.
Consolidate more workloads in a single environment
Greenplum reduces data silos by providing you with a single, scale-out environment for converging analytic and operational workloads, like streaming ingestion. Execute point queries, fast data ingestion, data science exploration, and long-running reporting queries with greater scale and concurrency.
Run analytics on public and private clouds, Kubernetes, or on-premises
Greenplum provides your enterprise with flexibility and choice because it can be deployed on all major public and private cloud platforms, on-premises, and with container orchestration systems like Kubernetes. Deploy and manage hundreds of Greenplum instances easily.
Pre-integrated components for easier consumption
VMware Tanzu Greenplum is based on PostgreSQL and the Greenplum Database project. It offers optional use-case specific extensions like PostGIS for geospatial analysis, and GPText (based on Apache Tika and Apache Solr) for document extraction, search, and natural language processing. These are pre-integrated to ensure a consistent experience, not a “wild-west,” DIY open source approach. Instead of depending on expensive proprietary databases, users can benefit from the contributions of a vibrant community of developers.
Streamline data science operations and simplify workflows
Tackle data science from experimentation to massive deployment with Apache MADlib, the open source library of in-cluster machine learning functions for the Postgres family of databases. MADlib with Greenplum provides multi-node, multi-GPU and deep learning capabilities. It also offers automation-friendly features such as model versioning, and the capability to push models from training to production via a REST API. Users avoid the pain of porting and re-coding analytical models.
“Whatever use case we can dream up and whatever ways we can think of to better understand the user, Greenplum allows us to do it.”
With support for advanced algorithms such as multi-layer perceptron and convolutional neural networks in Apache MADlib, users can begin to tackle cutting edge use cases in speech recognition, image recognition, machine translation, and computer vision. With optional support for REST APIs, you can train, test, and deploy in a single language (SQL), reducing the occurrence of errors when putting models into production at scale.
Move your analytics workloads to the platform of your choice under the terms and in the timeframes you choose. Deploy in Kubernetes, AWS, Microsoft Azure, GCP, private clouds, or on-premises with GBB. Have the freedom to select the best platform for each project and workload based on ease of use, performance, and total cost of ownership (TCO).
Replatform legacy enterprise data warehouses (EDWs) to replace expensive, proprietary databases. Modernize with the only open source-based, multi-cloud platform for analytics offering the full range of data warehouse functionality that your enterprise demands. Gain the power of an MPP system in conjunction with proven technology to reduce the cost and complexity of application migration.
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