GemFire

Pivotal GemFire is a distributed data management platform. Pivotal GemFire is designed for many diverse data management situations, but is especially useful for high-volume, latency-sensitive, mission-critical, transactional systems.

 Key Features and Functionality
    

•         Monitoring and Management
•         Native support for JSON Documents
•         New HTML5 based dashboard
•         Enhanced Parallel Disk Persistence
•         Spring Integration and Simplified APIs for Greater Development Ease
•         Scale-out Capabilities
•         Co-located Transactions to Dramatically Boost Throughput
•         Very High Throughput
•         Low and Predictable Latency
•         High Scalability
•         Continuous Availability
•         Heterogeneous Data Sharing
•         Wide Area Data Distribution
•         Native Support for Memcached Clients by Using Gemcached
•         HTTP Session Management for Tomcat and Pivotal tc Server
•         L2 Caching for Hibernate

References :http://www.vmware.com/in/products/vfabric-gemfire/features.html

Key Features and Functionality

Monitoring and Management

Monitor the current status of the entire Pivotal® GemFire® deployment through a visual dashboard. For command-line users, the Pivotal GemFire Shell ('gfsh') delivers a powerful interface to manage Pivotal GemFire deployments. Wth gfsh, Pivotal GemFire servers can be started and stopped, members can be configured, metrics viewed and access to most all other product capabilities available. View running Pivotal GemFire systems with the visually stunning new dashboard.

Native support for JSON Documents

Pivotal GemFire can store JSON documents along with key-value/object data. For developers writing mobile and other applications, this is very useful. Some of the capabilities provided to JSON documents include the ability to query within and across JSON documents, federated queries with support for joins across JSON and key-value stores and transactional support.

New HTML5 based dashboard

A simplified JMX model with federated MBeans provides a single-agent consolidated view of a Pivotal GemFire distributed system – integrated with gfsh and new dashboard.

Enhanced Parallel Disk Persistence

The "shared nothing" parallel disk persistence model provides persistence for any block of data: partitioned or replicated. This enables all your operational data to safely "live" in Pivotal GemFire, greatly reducing costs by relegating the database to an archival store.

Spring Integration and Simplified APIs for Greater Development Ease

Thanks to the Spring Data GemFire project, developers will be able to easily build Spring applications that leverage Pivotal GemFire distributed data management. Developers can architect their applications so that data access and business logic are separated from configuration and operation code. In addition, Pivotal GemFire APIs and related code samples help developers get productive quickly.

Scale-out Capabilities

Subscription processing is partitioned to enable access by many more subscribers with even lower latency than before. Clients communicate directly with each data-hosting server in a single hop, increasing access performance 2 to 3 times for thin clients.

Co-located Transactions to Dramatically Boost Throughput

Multiple transactions can be executed simultaneously across several partitioned regions.

Very High Throughput

Pivotal GemFire uses concurrent main-memory data structures and a highly optimized distribution infrastructure, offering 10X or more read and write throughput compared with traditional disk-based databases.

Low and Predictable Latency

Pivotal GemFire uses a highly optimized caching layer designed to minimize context switches among threads and processes.

High Scalability

• Scalability is achieved through dynamic partitioning of data across many member nodes and spreading the data load across the servers.
• For 'hot' data, the system can be dynamically expanded to have more copies of the data.
• Application behavior can also be provisioned and routed to run in a distributed manner in proximity to the data it depends on.

Continuous Availability

• In addition to guaranteed consistent copies of data in memory across servers and nodes, applications can synchronously or asynchronously persist the data to disk on one or more nodes.
• Pivotal GemFire's shared-nothing disk architecture ensures very high levels of data availability.

Heterogeneous Data Sharing

C#, C++ and Java applications can share business objects with each other without going through a transformation layer such as SOAP or XML. A change to a business object in one language can trigger reliable notifications in applications written in the other supported languages.

Wide Area Data Distribution

Pivotal GemFire's WAN gateway allows distributed systems to scale out in an unbounded and loosely-coupled fashion without loss of performance, reliability and data consistency.

Native Support for Memcached Clients by Using Gemcached

Use any memcached client to connect to Pivotal GemFire. Pivotal GemFire listens for memcached clients on a specified port, eliminating client configuration on memcahed clients.

HTTP Session Management for Tomcat and Pivotal tc Server

Pivotal GemFire lets you decouple session management from your JSP container. You can scale application server and HTTP session handling independently, leveraging Pivotal GemFire's ability to manage very large sessions with high performance and no session loss. Pivotal GemFire HTTP Session Management is pre-configured and can launch automatically with tc Server. For Tomcat, the module is enabled via minor configuration modifications.

• Watch a Demo on HTTP Session Management and GemFire VIDEO

L2 Caching for Hibernate

With L2 caching, developers can implement Pivotal GemFire's enterprise-class data management features for their Spring Hibernate applications. Highly scalable and reliable Pivotal GemFire L2 caching vastly increases Hibernate performance, reduces database bottlenecks, boosts developer productivity, and supports cloud-scale deployment.

- See more at: http://www.vmware.com/in/products/vfabric-gemfire/features.html#sthash.DTYtl4bW.dpuf

Key Features and Functionality

Monitoring and Management

Monitor the current status of the entire Pivotal® GemFire® deployment through a visual dashboard. For command-line users, the Pivotal GemFire Shell ('gfsh') delivers a powerful interface to manage Pivotal GemFire deployments. Wth gfsh, Pivotal GemFire servers can be started and stopped, members can be configured, metrics viewed and access to most all other product capabilities available. View running Pivotal GemFire systems with the visually stunning new dashboard.

Native support for JSON Documents

Pivotal GemFire can store JSON documents along with key-value/object data. For developers writing mobile and other applications, this is very useful. Some of the capabilities provided to JSON documents include the ability to query within and across JSON documents, federated queries with support for joins across JSON and key-value stores and transactional support.

New HTML5 based dashboard

A simplified JMX model with federated MBeans provides a single-agent consolidated view of a Pivotal GemFire distributed system – integrated with gfsh and new dashboard.

Enhanced Parallel Disk Persistence

The "shared nothing" parallel disk persistence model provides persistence for any block of data: partitioned or replicated. This enables all your operational data to safely "live" in Pivotal GemFire, greatly reducing costs by relegating the database to an archival store.

Spring Integration and Simplified APIs for Greater Development Ease

Thanks to the Spring Data GemFire project, developers will be able to easily build Spring applications that leverage Pivotal GemFire distributed data management. Developers can architect their applications so that data access and business logic are separated from configuration and operation code. In addition, Pivotal GemFire APIs and related code samples help developers get productive quickly.

Scale-out Capabilities

Subscription processing is partitioned to enable access by many more subscribers with even lower latency than before. Clients communicate directly with each data-hosting server in a single hop, increasing access performance 2 to 3 times for thin clients.

Co-located Transactions to Dramatically Boost Throughput

Multiple transactions can be executed simultaneously across several partitioned regions.

Very High Throughput

Pivotal GemFire uses concurrent main-memory data structures and a highly optimized distribution infrastructure, offering 10X or more read and write throughput compared with traditional disk-based databases.

Low and Predictable Latency

Pivotal GemFire uses a highly optimized caching layer designed to minimize context switches among threads and processes.

High Scalability

• Scalability is achieved through dynamic partitioning of data across many member nodes and spreading the data load across the servers.
• For 'hot' data, the system can be dynamically expanded to have more copies of the data.
• Application behavior can also be provisioned and routed to run in a distributed manner in proximity to the data it depends on.

Continuous Availability

• In addition to guaranteed consistent copies of data in memory across servers and nodes, applications can synchronously or asynchronously persist the data to disk on one or more nodes.
• Pivotal GemFire's shared-nothing disk architecture ensures very high levels of data availability.

Heterogeneous Data Sharing

C#, C++ and Java applications can share business objects with each other without going through a transformation layer such as SOAP or XML. A change to a business object in one language can trigger reliable notifications in applications written in the other supported languages.

Wide Area Data Distribution

Pivotal GemFire's WAN gateway allows distributed systems to scale out in an unbounded and loosely-coupled fashion without loss of performance, reliability and data consistency.

Native Support for Memcached Clients by Using Gemcached

Use any memcached client to connect to Pivotal GemFire. Pivotal GemFire listens for memcached clients on a specified port, eliminating client configuration on memcahed clients.

HTTP Session Management for Tomcat and Pivotal tc Server

Pivotal GemFire lets you decouple session management from your JSP container. You can scale application server and HTTP session handling independently, leveraging Pivotal GemFire's ability to manage very large sessions with high performance and no session loss. Pivotal GemFire HTTP Session Management is pre-configured and can launch automatically with tc Server. For Tomcat, the module is enabled via minor configuration modifications.

• Watch a Demo on HTTP Session Management and GemFire VIDEO

L2 Caching for Hibernate

With L2 caching, developers can implement Pivotal GemFire's enterprise-class data management features for their Spring Hibernate applications. Highly scalable and reliable Pivotal GemFire L2 caching vastly increases Hibernate performance, reduces database bottlenecks, boosts developer productivity, and supports cloud-scale deployment.

- See more at: http://www.vmware.com/in/products/vfabric-gemfire/features.html#sthash.DTYtl4bW.dpuf

http://gemfire.docs.pivotal.io/index.html
http://pivotal.io/big-data/datasheet/pivotal-gemfire
https://pubs.vmware.com/vfabric5/index.jsp?topic=/com.vmware.vfabric.gemfire.6.6/deploying/gfsh/gfsh_install_config.html


Tutorial
http://blog.pivotal.io/labs/labs/gemfire_introduction
http://gemfire702.docs.pivotal.io/7.0.2/userguide/getting_started/15_minute_quickstart.html
http://gemfire81.docs.pivotal.io/latest/userguide/tools_modules/pulse/quickstart.html

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Installing Cassandra on ubantu

Prerequisite already installed Java

java -version
echo $JAVA_HOME

 Installing Cassandra

To install Cassandra, download the binary files from the website, unpack them and move it to your personal folder:

cd ~/temp
wget http://www.us.apache.org/dist/cassandra/1.2.16/apache-cassandra-1.2.16-bin.tar.gz
tar -xvzf apache-cassandra-2.2.0-bin.tar.gz

 mv apache-cassandra-2.2.0 ~/cassandra

Next, make sure that the folders Cassandra accesses, such as the log folder, exists and that Cassandra has the right to write on it:

sudo mkdir /var/lib/cassandra
sudo mkdir /var/log/cassandra
sudo chown -R $USER:$GROUP /var/lib/cassandra
sudo chown -R $USER:$GROUP /var/log/cassandra

Now set Cassandra’s variables by running:

export CASSANDRA_HOME=~/cassandra
export PATH=$PATH:$CASSANDRA_HOME/bin

You’re going to need to configure Cassandra’s per-thread stack size to a larger one than default. Do so by running:

nano ~/cassandra/conf/cassandra-env.sh

and scrolling down to the line that says:

JVM_OPTS="$JVM_OPTS -Xss180k"

and changing it to:

JVM_OPTS="$JVM_OPTS -Xss280k"

like the image below:
Simply press CTRL+O to save and CTRL+X to exit.

Running Cassandra

To run a single-node test cluster of Cassandra, you aren’t going to need to change anything on the cassandra.yaml file. Simply run:

sudo sh ~/cassandra/bin/cassandra

and then run:

sudo sh ~/cassandra/bin/cassandra-cli

and if it says "Connected to: 'Test Cluster'" as it does on the image below, you are now running your single-node cluster.

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