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From dschnei...@apache.org
Subject [36/51] [abbrv] geode git commit: GEODE-2562 CTR Revise docs Main Features section
Date Tue, 07 Mar 2017 19:21:59 GMT
GEODE-2562 CTR  Revise docs Main Features section

- Remove instances of GemFire
- Simplify some language
- Add a paragraph about Geode Native (clients in other languages)


Project: http://git-wip-us.apache.org/repos/asf/geode/repo
Commit: http://git-wip-us.apache.org/repos/asf/geode/commit/319304e2
Tree: http://git-wip-us.apache.org/repos/asf/geode/tree/319304e2
Diff: http://git-wip-us.apache.org/repos/asf/geode/diff/319304e2

Branch: refs/heads/feature/GEM-1195
Commit: 319304e28fa33f685ccab51d7574fc8696cee50b
Parents: 635d311
Author: Karen Miller <kmiller@pivotal.io>
Authored: Wed Mar 1 14:21:42 2017 -0800
Committer: Karen Miller <kmiller@pivotal.io>
Committed: Wed Mar 1 14:28:25 2017 -0800

----------------------------------------------------------------------
 .../source/subnavs/geode-subnav.erb             |  2 +-
 .../getting_started/product_intro.html.md.erb   | 46 ++++++++++++--------
 2 files changed, 30 insertions(+), 18 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/geode/blob/319304e2/geode-book/master_middleman/source/subnavs/geode-subnav.erb
----------------------------------------------------------------------
diff --git a/geode-book/master_middleman/source/subnavs/geode-subnav.erb b/geode-book/master_middleman/source/subnavs/geode-subnav.erb
index 3711fff..5f03ee6 100644
--- a/geode-book/master_middleman/source/subnavs/geode-subnav.erb
+++ b/geode-book/master_middleman/source/subnavs/geode-subnav.erb
@@ -30,7 +30,7 @@ limitations under the License.
                         <a href="/docs/guide/11/getting_started/geode_overview.html">About
Apache Geode</a>
                     </li>
                     <li>
-                        <a href="/docs/guide/11/getting_started/product_intro.html">Main
Features of Apache Geode</a>
+                        <a href="/docs/guide/11/getting_started/product_intro.html">Main
Features</a>
                     </li>
                     <li class="has_submenu">
                         <a href="/docs/guide/11/prereq_and_install.html">Prerequisites
and Installation Instructions</a>

http://git-wip-us.apache.org/repos/asf/geode/blob/319304e2/geode-docs/getting_started/product_intro.html.md.erb
----------------------------------------------------------------------
diff --git a/geode-docs/getting_started/product_intro.html.md.erb b/geode-docs/getting_started/product_intro.html.md.erb
index 471bd42..103b2dd 100644
--- a/geode-docs/getting_started/product_intro.html.md.erb
+++ b/geode-docs/getting_started/product_intro.html.md.erb
@@ -1,5 +1,5 @@
 ---
-title:  Main Features of Apache Geode
+title:  Main Features
 ---
 
 <!--
@@ -19,7 +19,7 @@ See the License for the specific language governing permissions and
 limitations under the License.
 -->
 
-This section summarizes the main features and key functionality of Apache Geode.
+This section summarizes main features and key functionality.
 
 -   [High Read-and-Write Throughput](product_intro.html#concept_3B5E445B19884680900161BDF25E32C9__section_CF0E3E5C4F884374B8F2F536DD2A375C)
 -   [Low and Predictable Latency](product_intro.html#concept_3B5E445B19884680900161BDF25E32C9__section_9C5D669B583646F1B817284EB494DDA7)
@@ -33,38 +33,39 @@ This section summarizes the main features and key functionality of Apache
Geode.
 -   [Client/Server Security](product_intro.html#concept_3B5E445B19884680900161BDF25E32C9__section_577F601BC9854AA6B53CD3440F9B9A6A)
 -   [Multisite Data Distribution](product_intro.html#concept_3B5E445B19884680900161BDF25E32C9__section_091A306900D7402CAE5A46B5F9BFD612)
 -   [Continuous Querying](product_intro.html#concept_3B5E445B19884680900161BDF25E32C9__section_FF4C3B6E26104C4D93186F6FFE22B321)
+-   [Heterogeneous Data Sharing](product_intro.html#mainfeatures_heterogeneousdatasharing)
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_CF0E3E5C4F884374B8F2F536DD2A375C"
class="no-quick-link"></a>High Read-and-Write Throughput
 
-Geode uses concurrent main-memory data structures and a highly optimized distribution infrastructure
to provide read-and-write throughput. Applications can make copies of data dynamically in
memory through synchronous or asynchronous replication for high read throughput or partition
the data across many Geode system members to achieve high read-and-write throughput. Data
partitioning doubles the aggregate throughput if the data access is fairly balanced across
the entire data set. Linear increase in throughput is limited only by the backbone network
capacity.
+Read-and-write throughput is provided by concurrent main-memory data structures and a highly
optimized distribution infrastructure. Applications can make copies of data dynamically in
memory through synchronous or asynchronous replication for high read throughput or partition
the data across many system members to achieve high read-and-write throughput. Data partitioning
doubles the aggregate throughput if the data access is fairly balanced across the entire data
set. Linear increase in throughput is limited only by the backbone network capacity.
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_9C5D669B583646F1B817284EB494DDA7"
class="no-quick-link"></a>Low and Predictable Latency
 
-Geode's optimized caching layer minimizes context switches between threads and processes.
It manages data in highly concurrent structures to minimize contention points. Communication
to peer members is synchronous if the receivers can keep up, which keeps the latency for data
distribution to a minimum. Servers manage object graphs in serialized form to reduce the strain
on the garbage collector.
+The optimized caching layer minimizes context switches between threads and processes. It
manages data in highly concurrent structures to minimize contention points. Communication
to peer members is synchronous if the receivers can keep up, which keeps the latency for data
distribution to a minimum. Servers manage object graphs in serialized form to reduce the strain
on the garbage collector.
 
-Geode partitions subscription management (interest registration and continuous queries) across
server data stores, ensuring that a subscription is processed only once for all interested
clients. The resulting improvements in CPU use and bandwidth utilization improve throughput
and reduce latency for client subscriptions.
+Subscription management (interest registration and continuous queries) is partitioned across
server data stores, ensuring that a subscription is processed only once for all interested
clients. The resulting improvements in CPU use and bandwidth utilization improve throughput
and reduce latency for client subscriptions.
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_EF7A73D35D1241289C9CA19EDDEBE959"
class="no-quick-link"></a>High Scalability
 
-Geode achieves scalability through dynamic partitioning of data across many members and spreading
the data load uniformly across the servers. For "hot" data, you can configure the system to
expand dynamically to create more copies of the data. You can also provision application behavior
to run in a distributed manner in close proximity to the data it needs.
+Scalability is achieved through dynamic partitioning of data across many members and spreading
the data load uniformly across the servers. For "hot" data, you can configure the system to
expand dynamically to create more copies of the data. You can also provision application behavior
to run in a distributed manner in close proximity to the data it needs.
 
 If you need to support high and unpredictable bursts of concurrent client load, you can increase
the number of servers managing the data and distribute the data and behavior across them to
provide uniform and predictable response times. Clients are continuously load balanced to
the server farm based on continuous feedback from the servers on their load conditions. With
data partitioned and replicated across servers, clients can dynamically move to different
servers to uniformly load the servers and deliver the best response times.
 
-You can also improve scalability by implementing asynchronous "write behind" of data changes
to external data stores, like a database. Geode avoids a bottleneck by queuing all updates
in order and redundantly. You can also conflate updates and propagate them in batch to the
database.
+You can also improve scalability by implementing asynchronous "write behind" of data changes
to external data stores, like a database. This avoids a bottleneck by queuing all updates
in order and redundantly. You can also conflate updates and propagate them in batch to the
database.
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_CEB4ABFF83054AF6A47EA2FA09C240B1"
class="no-quick-link"></a>Continuous Availability
 
-In addition to guaranteed consistent copies of data in memory, applications can persist data
to disk on one or more Geode members synchronously or asynchronously by using Geode's "shared
nothing disk architecture." All asynchronous events (store-forward events) are redundantly
managed in at least two members such that if one server fails, the redundant one takes over.
All clients connect to logical servers, and the client fails over automatically to alternate
servers in a group during failures or when servers become unresponsive.
+In addition to guaranteed consistent copies of data in memory, applications can persist data
to disk on one or more members synchronously or asynchronously by using a "shared nothing
disk architecture." All asynchronous events (store-forward events) are redundantly managed
in at least two members such that if one server fails, the redundant one takes over. All clients
connect to logical servers, and the client fails over automatically to alternate servers in
a group during failures or when servers become unresponsive.
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_86D2B8CC346349F3913209AF87648A02"
class="no-quick-link"></a>Reliable Event Notifications
 
 Publish/subscribe systems offer a data-distribution service where new events are published
into the system and routed to all interested subscribers in a reliable manner. Traditional
messaging platforms focus on message delivery, but often the receiving applications need access
to related data before they can process the event. This requires them to access a standard
database when the event is delivered, limiting the subscriber by the speed of the database.
 
-Geode offers data and events through a single system. Data is managed as objects in one or
more distributed data regions, similar to tables in a database. Applications simply insert,
update, or delete objects in data regions, and the platform delivers the object changes to
the subscribers. The subscriber receiving the event has direct access to the related data
in local memory or can fetch the data from one of the other members through a single hop.
+Data and events are offered through a single system. Data is managed as objects in one or
more distributed data regions, similar to tables in a database. Applications simply insert,
update, or delete objects in data regions, and the platform delivers the object changes to
the subscribers. The subscriber receiving the event has direct access to the related data
in local memory or can fetch the data from one of the other members through a single hop.
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_A65B5F0DE8BF4AA6AFF16E3A75D4E0AD"
class="no-quick-link"></a>Parallelized Application Behavior on Data Stores
 
-You can execute application business logic in parallel on the Geode members. Geode's data-aware
function-execution service permits execution of arbitrary, data-dependent application functions
on the members where the data is partitioned for locality of reference and scale.
+You can execute application business logic in parallel on members. The data-aware function-execution
service permits execution of arbitrary, data-dependent application functions on the members
where the data is partitioned for locality of reference and scale.
 
 By colocating the relevant data and parallelizing the calculation, you increase overall throughput.
The calculation latency is inversely proportional to the number of members on which it can
be parallelized.
 
@@ -72,9 +73,9 @@ The fundamental premise is to route the function transparently to the applicatio
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_97CABBFF553647F6BBBC40AA7AF6D4C7"
class="no-quick-link"></a>Shared-Nothing Disk Persistence
 
-Each Geode system member manages data on disk files independent of other members. Failures
in disks or cache failures in one member do not affect the ability of another cache instance
to operate safely on its disk files. This "shared nothing" persistence architecture allows
applications to be configured such that different classes of data are persisted on different
members across the system, dramatically increasing the overall throughput of the application
even when disk persistence is configured for application objects.
+Each distributed system member manages data on disk files independent of other members. Failures
in disks or cache failures in one member do not affect the ability of another cache instance
to operate safely on its disk files. This "shared nothing" persistence architecture allows
applications to be configured such that different classes of data are persisted on different
members across the system, dramatically increasing the overall throughput of the application
even when disk persistence is configured for application objects.
 
-Unlike a traditional database system, Geode does not manage data and transaction logs in
separate files. All data updates are appended to files that are similar to transactional logs
of traditional databases. You can avoid disk-seek times if the disk is not concurrently used
by other processes, and the only cost incurred is the rotational latency.
+Unlike a traditional database system, separate files are not used to manage data and transaction
logs. All data updates are appended to files that are similar to transactional logs of traditional
databases. You can avoid disk-seek times if the disk is not concurrently used by other processes,
and the only cost incurred is the rotational latency.
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_FCB2640F1BED4692A93F9300A41CE70D"
class="no-quick-link"></a>Reduced Cost of Ownership
 
@@ -86,16 +87,27 @@ Clients can send individual data requests directly to the server holding
the dat
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_577F601BC9854AA6B53CD3440F9B9A6A"
class="no-quick-link"></a>Client/Server Security
 
-Geode supports running multiple, distinct users in client applications. This feature accommodates
installations in which Geode clients are embedded in application servers and each application
server supports data requests from many users. Each user may be authorized to access a small
subset of data on the servers, as in a customer application where each customer can access
only their own orders and shipments. Each user in the client connects to the server with its
own set of credentials and has its own access authorization to the server cache.
-
-Client/server communication has increased security against replay attacks. The server sends
the client a unique, random identifier with each response to be used in the next client request.
Because of the identifier, even a repeated client operation call is sent as a unique request
to the server.
+There may be multiple, distinct users in client applications. This feature accommodates installations
in which clients are embedded in application servers and each application server supports
data requests from many users. Each user may be authorized to access a small subset of data
on the servers, as in a customer application where each customer can access only their own
orders and shipments. Each user in the client connects to the server with its own set of credentials
and has its own access authorization to the server cache.
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_091A306900D7402CAE5A46B5F9BFD612"
class="no-quick-link"></a>Multisite Data Distribution
 
-Scalability problems can result from data sites being spread out geographically across a
wide-area network (WAN). GemFire offers a model to address these topologies, ranging from
a single peer-to-peer cluster to reliable communications between data centers across the WAN.
This model allows distributed systems to scale out in an unbounded and loosely coupled fashion
without loss of performance, reliability or data consistency.
+Scalability problems can result from data sites being spread out geographically across a
wide-area network (WAN). Models address these topologies, ranging from a single peer-to-peer
cluster to reliable communications between data centers across the WAN. This model allows
distributed systems to scale out in an unbounded and loosely coupled fashion without loss
of performance, reliability or data consistency.
 
-At the core of this architecture is the gateway sender configuration used for distributing
region events to a remote site. You can deploy gateway sender instances in parallel, which
enables GemFire to increase the throughput for distributing region events across the WAN.
You can also configure gateway sender queues for persistence and high availability to avoid
data loss in the case of a member failure.
+At the core of this architecture is the gateway sender configuration used for distributing
region events to a remote site. You can deploy gateway sender instances in parallel, which
enables an increase in throughput for distributing region events across the WAN. You can also
configure gateway sender queues for persistence and high availability to avoid data loss in
the case of a member failure.
 
 ## <a id="concept_3B5E445B19884680900161BDF25E32C9__section_FF4C3B6E26104C4D93186F6FFE22B321"
class="no-quick-link"></a>Continuous Querying
 
 In messaging systems like Java Message Service, clients subscribe to topics and queues. Any
message delivered to a topic is sent to the subscriber. Geode allows continuous querying by
having applications express complex interest using Object Query Language.
+
+## <a id="mainfeatures_heterogeneousdatasharing" class="no-quick-link"></a>Heterogeneous
Data Sharing
+
+C#, C++ and Java applications can share application business objects 
+without going through a transformation layer such as SOAP or XML.
+The server side behavior, though implemented in Java,
+provides a unique native cache for C++ and .NET applications.
+Application objects can be managed in the C++ process heap and 
+distributed to other processes using a common “on-the-wire” representation
+for objects.
+A C++ serialized object can be directly deserialized as an equivalent Java 
+or C# object.
+A change to a business object in one language can trigger reliable notifications in applications
written in the other supported languages.


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