Pivotal Big Data Suite Reviews & Pricing

by Pivotal Software, Inc. | Founded 2014, San Francisco, CA

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Overview Benefits Reviews Features

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What is Pivotal Big Data Suite?

Industry Specialties: Serves all industries

The Pivotal Big Data Suite is an integrated solution that enables big data management and analytics for enterprises. It includes Greenplum, a business-ready data warehouse, GemFire, an in-memory data grid and Postgres which helps deploy clusters of the PostgreSQL database. With a data architecture built for batch as well as streaming analytics, it can be deployed on-premise and in the cloud, and as part of Pivotal Cloud foundry.

Since 2019, Pivotal has been owned by VMWare. Besides an annual subscription, the vendor offers pricing by core for its computing resources. It is compatible with open data platform (ODP) versions of Hadoop and works with Apache Solr to provide text analytics.

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Pivotal Big Data Suite Benefits and Insights

Why use Pivotal Big Data Suite?

Key differentiators & advantages of Pivotal Big Data Suite

Open Source: Aligned with the PostGreSQL community, all open source contributions to the Greenplum database project share the same database core that includes the MPP architecture, analytical interfaces and security.
Flexible Deployment: Deploys seamlessly with Kubernetes by replacing StatefulSets with an automation layer. Available on AWS, Azure and Google Cloud Platform, it provides stateful data persistence to Cloud Foundry applications.
Advanced Analytics: Get deeper data insights through machine learning, deep learning, graph, text and statistical methods in one scale-out MPP database. Provides geospatial analytics based on open-source postGIS and text analytics through GPText with Apache Solr. Supports R and Python analytical libraries, as well as Keras and Tensorflow.
Scalability: Maximize efficiency and keep project costs low by scaling up or down and in or out on any on-premises or cloud computing environment. Its in-memory, horizontally scalable architecture is built from the ground up for low-latency applications, with rebalancing, cluster-to-cluster WAN connectivity and failover protocols in place.

Industry Expertise

The system provides big data analytics to clients in multiple industries around the world. These include government, financial services, pharmaceutical, IoT, cyber security and surveillance, oil and gas, communications, retail, transportation, healthcare, insurance, automotive and manufacturing.

Key Features

GemFire: Handles a large number of concurrent data requests with low-latency responses through parallel message queues and a scalable, event-driven architecture. Performs read and write operations at extremely high speeds through a distributed, in-memory, key-value store.
- Data Consistency: Ensures zero data loss in the event of a cluster failure through write-optimized disk-based persistence.
- Flexibility: Use any programming language — Ruby, Python, Scala and Node.JS — for high scale applications through its full-featured REST API.
- Analytics with Hadoop: With GemFire XD, it offers Hadoop persistence for big data use cases.
- Real-Time Event Notifications: React to changes in data as it comes into the system while reducing overhead on the SQL database.
Greenplum Database: Enables next-generation data warehousing and large-scale analytics through support for SQL, MapReduce parallel processing, and data values up to hundreds of terabytes.
- Command Center: Monitors performance metrics and individual cluster health and enables management task administration.
- Tanzu GPText: Joins the MPP database server with Apache SolrCloud enterprise search and the MADlib Analytics Library to enable free text search and analysis.
- Streaming Server: Ingests and transforms streaming data through extract, transform and load (ETL) into a target table.
- Connectors: Moves data in parallel and at high speeds to and from Apache Spark clusters to support interactive data analysis, in-memory analytics processing and batch and streaming ETL.
Query Optimizer: Automates parallel processing of data and queries and selects the best possible query execution model for optimal performance.

Limitations

At the time of this review, these are the limitations according to user feedback:

The latest version of Greenplum doesn’t bundle cURL and instead loads the system-provided library.
Doesn’t support upgrading a previous version of the Greenplum database to the current one.
MADlib, GPText and PostGIS aren’t available for Ubuntu systems.
Greenplum for Kubernetes isn’t provided for the latest release.

Suite Support

Go through the free webinars, knowledge base, ebooks, white papers, podcasts, videos, slides and support community resources for issue resolution and answers to queries.

All subscribers have 24/7, 365-days access to global product experts and online peer and self-solve resources. Sign up for the App Modernization Technical Account Management (AM TAM) service that provides 9 a.m. — 5 p.m. access to a technical account manager, weekly carelog reviews, root cause analysis and upgrade coordination.

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Training: Go through the Tanzu TV and Guide resources that are available for free on the developer center on the vendor’s website, or sign up for workshops. Join instructor-led training at the online KubeAcademy for Kubernetes courses.

Tickets: Submit a support request by logging in to a Pivotal account.