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VMWare launches Greenplum 7, an open source AI analysis platform, to improve scalability and multi-load processing capacity

2025-01-22 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > IT Information >

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CTOnews.com, October 13, according to the official account of VMWare China R & D Center, VMware Greenplum 7 has been officially launched, which is a "unified analysis and artificial intelligence" platform that supports vector data parallel processing and claims to be "integrated with the latest large language modeling approach (LLM)" and "can help enterprises make full use of their data resources."

▲ Tupu VMWare China R & D Center VMware claimed that the Greenplum core is based on the open source PostgreSQL project, seamlessly integrates business intelligence (BI) and artificial intelligence (AI) functions on the same platform, unifies data analysis and artificial intelligence requirements, and all operations can be realized through the user's familiar SQL database interface.

VMware believes that Greenplum has significant flexibility in deployment, data processing advantages, the ability to manage "all types of data" and the integration of enhanced security features, enabling enterprises to respond to complex challenges efficiently and quickly.

The main updates of VMware Greenplum 7 attached to CTOnews.com are as follows:

VMware Greenplum 7, an open source and derivative of PostgreSQL 12, builds on open source code and takes advantage of the functionality, reliability, and flexibility of modern PostgreSQL versions. Compared with the previous version, Greenplum 7 is rooted in PostgreSQL 12 and integrates releases of PostgreSQL over the past five years.

Multiple index types VMware Greenplum 7 supports multiple index types, including B-tree index, hash index, bitmap index, block range index, text index, geospatial index, and AI vector index. This feature optimizes data retrieval and query performance. The Greenplum query optimizer has been improving since 2009, with a good performance record in version 6 and an extension in version 7 to provide comprehensive index selection support.

Using PXF to enhance data federation the platform extension Framework (PXF) in VMware Greenplum 7 has been improved to achieve excellent data federation. Enterprises can now query datasets in Amazon simple Storage Service (S3) object storage, Hadoop distributed file system (HDFS), and other relational databases through JDBC. It uses PostgreSQL's foreign data wrapper API to access remote data sources in parallel and provides an abstract data model to manage the security and statistical data of remote data to optimize queries.

Enhanced text search VMware Greenplum 7 extends text search while supporting lexical search and artificial intelligence-driven semantic search to provide more accurate search results. Lexical search supports traditional text search based on keywords, while semantic search is supported by artificial intelligence and vector embeddings.

Upgrade Geospatial Analysis VMware Greenplum 7 upgrades the geospatial analysis feature by integrating PostGIS version 3. This improvement greatly improves the speed and feature richness of geospatial query.

Row-level security permissions this feature complements the existing role-based security model in VMware Greenplum as well as table-level and column-level permissions.

The generation column VMware Greenplum 7, which is used to enhance data modeling, introduces the generation column, which improves data abstraction and modeling, and solves the use case problems such as security feature retention and data masking.

Improved DBA query function Greenplum 7 makes a number of improvements to DBA query capabilities, including UPSERT support, user-defined functions with transactions, and improvements to ALTER TABLE to reduce data rewriting.

Enhanced semi-structured and unstructured data analysis Greenplum 7 supports semi-structured data processing such as enhanced JSON and array data processing in addition to XML documents. Full-text search and text-based lexical search index can achieve efficient text storage, indexing and search. In addition, vector embedding enables the condensation and efficient representation of unstructured data, allowing similarity search of matched documents, images and videos across multiple languages, including multilingual search.

More comprehensive PostgreSQL extension support for the PostgreSQL extension ecosystem, such as advanced password checking, fuzzy string matching, Hyperloglog, Ip4r for network data, Isn for media data, nanosecond timestamp, sparse vector, Tablefunc for perspective, UUID for unique identifiers, and pg_vector for artificial intelligence vector embedding, are all supported.

Advanced resource management Greenplum 7 introduces a series of advanced resource management functions. These features ensure robust performance under high loads.

The VMware vSphere deployment model Greenplum 7 can be deployed in a bare metal or public cloud environment with reference to the recommended architecture. The automated deployment model provided in the Greenplum 7 release can also be seamlessly integrated into the vSphere private cloud environment.

Multi-data center disaster recovery solution as part of a multi-data center disaster recovery solution, data is replicated through transaction log archiving to achieve a more efficient and lower recovery point objective (RPO) and recovery time objective (RTO) disaster recovery solution than previous versions of Greenplum.

The new extension PostgresML provides new user-defined functions that allow users to use tens of thousands of open source artificial intelligence / machine learning pre-training models in VMware Greenplum.

Referenc

VMware Greenplum 7 is officially released!

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