From d87cae0ba11d7ab66420f26edaeb232d8f68ffea Mon Sep 17 00:00:00 2001 From: Dave Barnes Date: Tue, 17 Nov 2015 13:13:57 -0800 Subject: [PATCH 1/3] GEODE-53: Text edit to Geode web pages. Fixed various typos, fleshed-out some links and descriptive text. Modified the README.md instructions for setting up the local webpage environment. --- gemfire-site/content/community/index.html | 8 ++--- gemfire-site/content/index.html | 29 +++++++++---------- gemfire-site/website/README.md | 3 +- .../website/content/community/index.html | 12 ++++---- gemfire-site/website/content/index.html | 29 +++++++++---------- 5 files changed, 40 insertions(+), 41 deletions(-) diff --git a/gemfire-site/content/community/index.html b/gemfire-site/content/community/index.html index 6492b8fa1705..8aa29ecf473c 100644 --- a/gemfire-site/content/community/index.html +++ b/gemfire-site/content/community/index.html @@ -242,9 +242,9 @@

Join Our Community of Contributors!

-

The Apache Geode team welcomes contributors who want to support the Geode technology. Our community builds everything from this website, to the Geode code, to documentation and best practices information.

+

The Apache Geode team welcomes contributors who want to support the Geode technology. Our community builds everything from this website, from the Geode code to documentation and best practices information.

-

We especially welcome additions and corrections to the documentation, wiki, and website to improve the user experience. Bug reports, and fixes and additions to the Apache Geode code are welcome. Helping users learn best practices also earns karma in our community.

+

We especially welcome additions and corrections to the documentation, wiki, and website to improve the user experience. Bug reports and fixes and additions to the Apache Geode code are welcome. Helping users learn best practices also earns karma in our community.

@@ -288,8 +288,8 @@

OSCON <

-

PJUG Meetup Portland, OR
July 20-24, 2015

-

Text text textText text textText text textText text textText text textText text text

+

PJUG Meetup Portland, OR
July 20-24, 2015

+

Joint meeting with co-hosted between OSCON, PJUG and PDXScala

 

diff --git a/gemfire-site/content/index.html b/gemfire-site/content/index.html index afaaa776c1ed..e8c877690f0f 100644 --- a/gemfire-site/content/index.html +++ b/gemfire-site/content/index.html @@ -73,10 +73,9 @@

Performance is key. Consistency is a must.

Solving the hardest data management problems since 2002.

Build elastic modern in-memory data intensive applications and scale.
- Delivery high-performance at cloud scale blending advanced techniques for data replication, partitioning and distributed processing. +
Deliver high-performance at cloud scale blending advanced techniques for data replication, partitioning and distributed processing.
-

- Offering a database-like consistency model, reliable transaction processing and shared nothing architecture at ease.

+
Implement a database-like consistency model, reliable transaction processing and shared-nothing architecture with ease.

@@ -95,52 +94,52 @@

Performance is key. Consistency is a must.

Replication and Partitioning

-

Data can easily be partitioned (sharded) or replicated and resilience is ensured through redundant copies or disk-persistency allowing data to scale however is needed.

+

Data can easily be partitioned (sharded) or replicated and resilience is ensured through redundant copies or disk-persistence allowing data to scale to fit any need.

Persistence

-

Super fast WAL persistence mechanism with shared-nothing architecture and optmized for fast parallel recovery of a cluster or single node.

+

Super fast WAL persistence mechanism with shared-nothing architecture optimized for fast parallel recovery of a cluster or a single node.

Performance

-

Predictable low-latency for transactions, reads, writes and query processing on top of index and non-indexed data.

+

Predictable low latency for transactions, reads, writes and query processing over indexed and non-indexed data.

-

In-Memory

-

Blazing fast in-memory storage optmized for larger heaps, with the option of using off-heap, compression and features such as disk-overflow, eviction and expiration.

+

In-Memory Storage

+

Blazing fast in-memory storage optimized for large heaps, with the option of using off-heap storage, compression and features such as disk-overflow, eviction and expiration.

Functions

-

Distributed data-aware processing can be deployed and executed in parallel on a cluster. In the case of failures, processing can be retried on different nodes.

+

Distributed data-aware processing can be deployed and executed in parallel on a cluster. Failed operations can be retried on different nodes.

Transactions

-

ACID distributed transactions allows for efficient and safe coordinated operations on colocated data. Transactions can be suspended, initiated from a client or a server.

+

ACID distributed transactions support for efficient and safe coordinated operations on colocated data. Transactions can be initiated from a client or a server and can be suspended.

OQL and Indexes

-

Object Query Language allows distributed query execution on hot and cold data, with SQL-like capabilities, including joins.
- Multiple option of indexes can be created and consistently maintained across the cluster.

+

Object Query Language supports distributed query execution on hot and cold data, with SQL-like capabilities, including joins.
+ Multiple indexes can be created and consistently maintained across the cluster.

Events

-

Clients can be notified about server-side data events, and servers can react synchronous or asynchronously with guaranteed delivery of ordered events.

+

Clients can be notified about server-side data events, and servers can react synchronously or asynchronously with guaranteed delivery of ordered events.

Clustering

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Highly scalable, battle-proof advanced clustering technology, with failure detection, dynamic scale, and network-partition detection algorithms.

+

Highly scalable, robust, advanced clustering technology with failure detection, dynamic scale, and network-partition detection algorithms.

@@ -164,7 +163,7 @@

Clustering

About the Project

Apache Geode is a data management platform that provides real-time, consistent access to data-intensive applications throughout widely distributed cloud architectures.

By pooling memory, CPU, network resources, and optionally local disk across multiple processes to manage application objects and behavior, it uses dynamic replication and data partitioning techniques to implement high availability, improved performance, scalability, and fault tolerance. In addition to being a distributed data container, Geode is an in-memory data management system that provides reliable asynchronous event notifications and guaranteed message delivery.

-

Apache Geode is an extremely mature and robust product that can trace its legacy all the way back to one of the first Object Databases for Smalltalk: GemStone. Geode (as GemFire™) was first deployed in the financial sector as the transactional, low-latency data engine used by multiple Wall Street trading platforms. Today Geode is used by over 600 enterprise customers for high-scale, 24x7 business critical applications.

+

Apache Geode is a mature mature and robust product that can trace its legacy all the way back to GemStone, one of the first Object Databases for Smalltalk. Geode (as GemFire™) was first deployed in the financial sector as the transactional, low-latency data engine used by multiple Wall Street trading platforms. Today Geode is used by over 600 enterprise customers for high-scale, 24x7 business critical applications.