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Pivotal Product Suite

Greenplum, Hawq, Pivotal HD, Gemfire, SQLFire, Redis

ZData offers consulting and managed services to help your company with product selection, installation, configuration, training, and is a reseller for not only Pivotal Greenplum® but the entire Pivotal Stack.  When you purchase software directly from zData your will receive 10% off Services! – Contact us for more information


ZData specialized in the Insight from Big Data is essential to business today. Predictive analytics of high volumes of data can make the difference between a profit or a loss, save lives, or predict the weather. Pivotal Greenplum® Database is a purpose-built, dedicated analytic data warehouse designed to extract value from your data.

The Pivotal Greenplum Database (Pivotal GPDB) manages, stores and analyzes terabytes to petabytes of data in large-scale analytic data warehouses around the world. Using the purpose-built Pivotal GPDB platform, your organization can experience 10x, 100x or even 1000x better performance over traditional RDBMS products. Pivotal GPDB extracts the data you need to determine which modern applications will best serve customers in context, at the right location, and during the right activities using a shared-nothing, massively parallel processing (MPP) architecture and flexible column- and row-oriented storage. It also leverages fully parallel communication with external databases and Hadoop to continually harness data. With Pivotal GPDB, your enterprise can rapidly develop deep analytics using preferred toolsets and languages that your team already knows, including SQL, Python, Ruby, and Java.


HAWQ integrates the industry’s first native, mature massively parallel processing (MPP) SQL query processor with Apache Hadoop. HAWQ enables you to leverage existing SQL-capable business intelligence and analytic tools and extract, load, transform (ETL) processes, plus your workforce’s SQL skills to simplify Hadoop-based data analytics development. This increases your team productivity and helps you reduce costs. HAWQ benefits include unprecedented query processing performance—100X improvement in query performance—as well as true, interactive and deep SQL processing, and powerful analytics. Unlike new SQL-on-Hadoop entrants, Pivotal HAWQ’s years of innovation have resulted in a rich, powerful SQL query optimizer and processor optimized to run analytical queries and mixed query workloads in massively parallel, distributed environments.

Pivotal HD

Pivotal HD is a commercially supported, enterprise-capable distribution of the Apache Hadoop stack. It includes Hadoop Distributed File System (HDFS), MapReduce, Hive, Pig, HBase, Zookeeper, Yarn and Mahout. Running Pivotal HD’s commercial Hadoop distribution on a Pivotal DCA helps you eliminate the pain associated with building out, debugging and monitoring Hadoop clusters from scratch, which is required by other distributions.

  • Hadoop Distributed File System (HDFS) – HDFS is a Java-based file system that provides scalable and reliable data storage. With industry installation in the thousands of nodes, HDFS has proven to be a solid foundation for any Hadoop deployment.
  • MapReduce – MapReduce is a Hadoop framework for easily writing applications that process large amounts of unstructured and structured data in parallel, in a reliable and fault-tolerant manner. The framework is resilient to hardware failures, handling them transparently from user applications.
  • Hive – Hive is a data warehouse system for Hadoop that facilitates easy data summarization, ad-hoc queries and the analysis of large datasets stored in Hadoop-compatible file systems. This SQL-like interface gives users a row-based storage capability, which, along with compression, results in an improved compression ratio for storing data.
  • Mahout – Mahout is a library of scalable machine-learning algorithms. Mahout’s core algorithms are for recommendation mining, clustering, classification and batched based collaborative filtering are implemented on top of the Hadoop using the map/reduce paradigm. The number of implemented algorithms is growing.
  • Pig – Pig is the procedural language for processing large, semi-structured data sets using the Hadoop MapReduce platform. It enables developers to more easily write MapReduce jobs by providing an alternative programming language to Java.
  • HBase – HBase is a distributed, versioned, column-oriented storage platform that provides random real-time read/write access to big data for user applications.
  • YARN – Hadoop YARN is a framework for job scheduling and cluster resource management. YARN stands for “Yet-Another-Resource-Negotiator.” It is a new framework that facilitates writing arbitrary distributed processing frameworks and applications. It frees up application framework developers to work on frameworks rather than minor details. Yarn is a subproject of Apache Hadoop.
  • Zookeeper – Zookeeper is a highly available system for coordinating distributed processes. Distributed applications use Zookeeper to store and mediate updates to key configuration information.
  • Flume – Flume is a distributed, reliable and available service for efficiently collecting, aggregating and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple, extensible data model that allows for online analytic application.

GemFire XD

The industry’s premier “In-memory with Big Data” relational OLTP data store, combining the power of storing and processing data in memory with the scale out persistence provided by Pivotal Hadoop. GemFire XD supports ANSI SQL and allows the creation of linearly scalable, highly available, elastic applications that have high throughput, low latency applications designed to run at cloud scale. GemFire XD comes with patent pending technology from GemFire that allows servers to host hundreds of gigs of data in memory in a single process without incurring the penalties usually associated with garbage collection issues in a JVM. (GemFire XD is a Java based product that runs in a stock JVM). This gives us the ability to create and manage large volumes of data in memory for transactional applications. GemFire XD allows the execution of parallel stored procedures on large volumes of data reducing network I/O and allowing everything from map-reduce like functions to arbitrary behavior execution on the data to run efficiently.