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Greenplum Database is an advanced, fully featured, open source data platform. It provides powerful and rapid analytics on petabyte scale data volumes.
• Analytical functions: t-statistics, p-values and naïve Bayes for advanced in-database anlytics • Workload management enables priority adjustment of running queries • Database performance monitor tool allows system administrators to pinpoint the cause of network issues, and separate hardware issues from software issues • Polymorphic data storage and execution • Trickle micro-batching allows data to be loaded at frequent intervals • Comprehensive SQL-92 and SQL-99 support with SQL 2003 OLAP extensions
• Open source
• Open source
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
What is best?
• Analytical functions: t-statistics, p-values and naïve Bayes for advanced in-database anlytics • Workload management enables priority adjustment of running queries • Database performance monitor tool allows system administrators to pinpoint the cause of network issues, and separate hardware issues from software issues
What are the benefits?
• Anywhere data access: Execute queries from the database against external data sources and return data in parallel regardless of location, format, or storage medium • In-database compression: Increase performance and dramatically reduce the space required to store data • Simple and automated: Tables are automatically distributed across nodes • Petabyte-Scale Loading: High-performance loading and unloading utilizing MPP Scatter/Gather Streaming technology
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Greenplum Database is a massively parallel processing (MPP) database server with an architecture specially designed to manage large-scale analytic data warehouses and business intelligence workloads.
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Greenplum Database is an advanced, fully featured, open source data platform. It provides powerful and rapid analytics on petabyte scale data volumes. Uniquely geared toward big data analytics, Greenplum Database is powered by the world’s most advanced cost-based query optimizer delivering high analytical query performance on large data volumes. The Greenplum Database architecture provides automatic parallelization of all data and queries in a scale-out, shared nothing architecture. High-performance loading uses MPP technology. Loading speeds scale with each additional node to greater than 10 terabytes per hour, per rack. The query optimizer available in Greenplum Database is the industry’s first cost-based query optimizer for big data workloads. It can scale interactive and batch mode analytics to large datasets in the petabytes without degrading query performance and throughput. Greenplum Database can use the append-optimized (AO) storage format for bulk loading and reading of data, and provides performance advantages over HEAP tables. All compression algorithms can be used with either row or column-oriented tables, but Run-Length Encoded (RLE) compression can only be used with column-oriented tables. Greenplum Database also can use declarative partitions and sub-partitions to implicitly generate partition constraints. Greenplum Database queries use a Volcano-style query engine model, where the execution engine takes an execution plan and uses it to generate a tree of physical operators, evaluates tables through physical operators, and delivers results in a query response. The Greenplum Database master is the entry to the Greenplum Database system, accepting client connections and SQL queries, and distributing work to the segment instances.
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