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Big Data Related Products

Pivotal GemFire

Scale-Out Real Time Innovation

Today's leading companies aren't only data driven, they are data centric. The market leaders are not only storing and analyzing data, they're putting into action through innovative next gen applications. Building and supporting those next gen applications is difficult and comes with bleeding edge requirements for scale, global reach, and unmatched performance. Business critical strategic applications, such as for financial trading, travel booking, and payment processing require data consistency - you can’t sell the same stock twice, or afford to lose your customers data. Developers of these applications must meet extremely high service level requirements. If these applications are unavailable, fail to perform, or mess up transactions, companies risk lost revenue, financial liabilities, and customer dissatisfaction.

Pivotal GemFire is the distributed, in-memory database for developers who are building the highest scaling and performing data-centric apps in the world. When you have to process hundreds of thousands of simultaneous transactions involving terabytes of operational data, you need a data management system that can deliver performance at scale, while ensuring consistency of data, and providing high availability and resiliency.

Pivotal customers using GemFire routinely:

PIVOTAL GemFire Features

Meet Highest Level Service Requirements for Data-Driven Custom Applications

Pivotal® GemFire® is an in-memory distributed database that is designed to provide:

  • Scale-Out Performance
  • Consistent database operations across globally distributed applications
  • High availability, resilience, and global scale
  • Powerful developer features
  • Easy administration of distributed nodes

The features of Pivotal GemFire that help customers achieve these capabilities include:

Scale-Out Performance

  • In-memory storage: all operational data compressed & available in-memory to avoid disk I/O penalty
  • Elastic, linear scalability: easily scale up or down capacity to meet changes in demand
  • Optimized data distribution & processing: configure data distribution across grid to optimize speed of data access & processing

Consistent Database Operations Across Globally Distributed Applications

  • Performance-optimized disk persistence: ensures durability of data with little cost to in-memory speed.
  • Configurable consistency: choose consistency model supporting distributed OLTP applications to balance performance and data availability.
  • Distributed queries: OQL queries of data over distributed nodes that can be optimized with indexes on key values

High Availability, Resilience, and Global Scale

  • Node fail-over: application and data access ensured in event of network split or node failure.
  • Resilient self-healing: fast node startup on reconnect, self-healing of clusters automates restoration after node failure.
  • Rolling upgrade: keep clusters running while serially updating individual nodes so no planned maintenance downtime is required.
  • Cluster to cluster WAN connectivity: enabling global scale of data access and multi-site capability.

Powerful Developer Features

  • Out of box caching: Session caching & L2 Hibernate support without changing code on Pivotal Tc Server
  • Language support: Java, C++, C# native programming language support
  • Data type support: user-defined objects, complex object graphs, JSON documents
  • APIs: Java Hashmap, Spring Data GemFire, REST, Memcached
  • Versioning of schema: system handles multiple application versions running simultaneously against data nodes
  • Powerful application functions: data-aware functions, scatter-gather functions, Object Query Language (OQL), publish & subscribe and continuous query event framework with reliable asynchronous queues for delivering events.

Easy Administration of Distributed Grids

  • Auto tuning: automatic distribution of data to optimize usage of system resources on nodes for best cluster performance
  • Cluster configuration service: configure all nodes in cluster from single fault-tolerant service
  • Cluster monitoring & data query: dashboard showing cluster & node status; view and query data in nodes
  • Performance statistics analysis: offline tool for viewing historical logs and statistics to diagnose bottlenecks
  • Command line tools: easy automation and scripting of administrative tasks via command line interface

PIVOTAL GemFire Technology

What is GemFire?

Pivotal GemFire is an in-memory distributed database for high scale custom applications. GemFire provides in-memory access for all operational data spread across hundreds of nodes with a “shared nothing” architecture. This enables GemFire to provide low latency data access to applications at massive scale with many concurrent transactions involving terabytes of operational data. Designed for maintaining consistency of concurrent operations across its distributed data nodes, Pivotal GemFire can support ACID transactions for massively scaled applications such as stock trading, financial payments, and ticket sales in proven customer deployments of more than 10 million user transactions a day. Originally developed to serve data for mission critical applications in the financial industry, GemFire offers built in fail-over and resilient self-healing clusters to allow developers to meet the most stringent service level requirements for data accessibility.

PIVOTAL GemFire Technology

Scale-Out Performance

In-Memory Storage

GemFire stores all required data in RAM memory across distributed nodes to provide fastest access to data while minimizing the performance penalty of reading from disk.

Elastic, Linear Scalability

GemFire provides linear scalability that allows you to predictably increase capacity for number of operations per second, and data storage simply by adding additional nodes to a cluster. Data distribution and system resource usage is automatically adjusted as nodes are added or removed, making it easy to scale up or down to quickly meet expected or unexpected spikes of demand.

Optimized Data Distribution Across Nodes

GemFire will automatically optimize how data is distributed across nodes to optimize latency and usage of system resources. You can also configure partitioning and replication of data to further optimize application response time. GemFire will appropriately direct processing operations on data to the specific nodes where data resides in order to reduce latency and network traffic.

PIVOTAL GemFire Technology

Consistent Database Operations Across Globally Distributed Applications

Performance-Optimized Persistence

To ensure durability of data in the event of node failure, GemFire writes to disk a log of all creates, updates, and deletes of data managed by a node. This log can then be read to reconstruct the last consistent state of the in-memory database on that node when a node comes back online.

Configurable Consistency

GemFire is capable of providing ACID consistency across distributed nodes to support high capacity transactional applications. You can also configure consistency models for higher performance such as allowing the entire grid to cache and operate on data, or turn consistency off for highest performance caching.

Distributed Queries and Regional Functions

Pivotal GemFire supports the Object Query Language (OQL) for authoring queries. Queries are sent to the appropriate nodes that serve relevant partitions of data. Query results are then merged and sent back to the client application. Developers can define indexes on key values to improve performance. In a similar fashion, when functions that operate on classes of data are invoked, processing will be routed to appropriate nodes responsible for serving partitions of targeted data.

PIVOTAL GemFire Technology

High Availability, Resilience, and Global Scale

Cluster Resilience and Fail Over

GemFire provides continuous uptime with built in high availability and disaster recovery. Multiple failure detection models detect and react to failures quickly, ensuring that the cluster is always available, and that the data set is always complete.

Resilient Self-Healing

GemFire self-healing automation allows a node to quickly rejoin a cluster once it becomes operational again, with fast startup, reconnect, and incremental updates of changed data, all handled without administrator intervention.

Rolling Upgrade

When it becomes time to deploy a new version of application or GemFire software, system administrators can take advantage of redundancy zones to update portions of a cluster automatically at the same time. The remaining redundant nodes can stay operational serving the application in a highly available manner. This means no planned maintenance downtime is required for version upgrades or patching.

Cluster-to-Cluster WAN Connectivity

GemFire allows multiple clusters to be connected via WAN gateways. This allows application data access to span across the globe, and allows companies to meet local data requirements, such as country-specific privacy regulations. WAN connected clusters also enable multi-site failover capability, ensuring ongoing availability and built-in disaster recovery in the case of catastrophic failure.

Example topologies of Pivotal GemFire deployments supporting different service level requirements of data-driven applications.

PIVOTAL GemFire Technology

Powerful Developer Features

Data Types, Language, and API Support

GemFire allows developers to manage data from user-defined classes as well as JSON documents. Native language clients and support are provided for Java, C++, and C# programming languages. Applications written in other programming languages can access the same features via a REST API. Other supported API’s include Java Hashmap, Memcached, and Spring Data GemFire.

Flexible Schemas and Versioning

GemFire schema serialization, called PDX, allows data types to be dynamically modified, such as when new kinds or version of an application are deployed against the same data nodes. The system automatically bridges between application versions allowing the different versions to work with the same data, since schema type information is dynamically discovered while processing queries from any version application. Data types in PDX are language independent, allowing applications written in any language to access the same data.

Out of Box Caching and Powerful Application Features

Developers can add GemFire caching to their applications running on Pivotal Tc Server with little or no modification to their application code. Tc Server will cache user sessions, even across web servers and data centers. Spring L2 Hibernate is also supported in Tc Server. Developers need only annotate their code to invoke this Spring framework capability.

GemFire provides powerful advanced application features to developers that want to leverage its distributed caching and database capabilities. Like many database platforms, developers can embed and generate queries, in Gemfire’s case using OQL. OQL can also be used to set up “continuous queries” that return a streaming result set updated whenever there are new entries meeting your query criteria. GemFire provides a sophisticated event handling mechanism providing a publish and subscribe approach and durable asynchronous queues suitable for mission critical application requirements.

PIVOTAL GemFire Technology

Easy Administration of Distributed Nodes

Automated Tuning & Simplified Cluster Configuration

GemFire is built to automate administrative tasks as much as possible. This includes automating tuning of system resources between nodes in a cluster by intelligently managing the placement of data while reducing network round trips. Data gets replicated only to those nodes that need the data, and requests for access are routed intelligently using the most direct path available. This data placement and resource allocation is adjusted automatically if nodes are added to, or removed from the cluster. Furthermore, node configuration is handled centrally with automatic redundancy for high-availability. New nodes can get their configuration from the centralized configuration manager upon startup to quickly join a cluster with no additional system administration tasks.

Comprehensive Monitoring & Administration Tools

GemFire provides a comprehensive set of online and offline tools for monitoring and administering clusters. The online dashboard allows drill down into cluster and node status, and querying of stored data. The offline analytics tool allows diagnosis of system bottlenecks through analysis of historical statistics logging. A command line tool allows administrators to take action on clusters and nodes such as starting, stopping and configuring settings.

Flexible Deployment Options

GemFire runs in Java Virtual Machines in 32 and 64-bit mode on Windows, Linux, and Solaris operating systems. Client nodes running in C++, C#, .Net, and Java are supported. Other popular web-scale programming languages such as Ruby, Node.JS, Scala, and Python can access GemFire capabilities via Rest API. GemFire grids can be set up with active/active multi-site bi-directional WAN replication to enable disaster recovery, business continuity, and geographical proximity for lowest possible latency world-wide.


News and events, blog posts, videos, case studies, whitepapers, and other related resources.


Distributed In-Memory Data Management Solution Improves the Capacity and Availab...

Case Study |

Pivotal Big Data Suite Gets Real Time Boost with In-Memory Upgrade

Press Release |

Today Pivotal is announcing the release of Pivotal GemFire 8, part of Pivotal Big Data Suite.

Blog Post | Sep 23, 2014

DATA SHEET - Pivotal GemFire

Datasheet |

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