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The following commit(s) were added to refs/heads/master by this push:
new 980c20e Updated the in-memory data grid page.
980c20e is described below
commit 980c20e767d0bcf5185d8661fabfdd8d12bd47ba
Author: Denis Magda <[email protected]>
AuthorDate: Tue Jul 20 17:45:30 2021 +0300
Updated the in-memory data grid page.
---
use-cases/in-memory-data-grid.html | 78 ++++++++++++++++++--------------------
1 file changed, 36 insertions(+), 42 deletions(-)
diff --git a/use-cases/in-memory-data-grid.html
b/use-cases/in-memory-data-grid.html
index 9c1e16e..dc5e7e9 100644
--- a/use-cases/in-memory-data-grid.html
+++ b/use-cases/in-memory-data-grid.html
@@ -59,59 +59,53 @@ under the License.
<div class="container">
<p>
- The Apache Ignite® in-memory data grid accelerates and scales your
databases, services,
- and APIs. It supports key-value and ANSI SQL APIs, ACID
transactions, co-located processing,
- and machine learning libraries. As an in-memory data grid, Ignite
is frequently used to increase the performance and
- scalability of existing real-time applications, for <a
href="/use-cases/high-performance-computing.html">
- high-performance computing</a>, or for caching of data scattered
across databases.
+ Apache Ignite can be used as an in-memory data grid that
accelerates and scales your existing databases and
+ data stores. The grid supports key-value and ANSI SQL APIs, ACID
transactions, co-located processing,
+ and machine learning libraries. As an in-memory data grid, Ignite
is frequently used to increase the
+ performance and scalability of real-time applications, to support
<a href="/use-cases/high-performance-computing.html">
+ high-performance computing</a>, and to cache data that is
scattered across databases.
</p>
<img class="img-fluid diagram-right"
src="/images/svg-diagrams/data_grid.svg" alt="In-Memory Data Grid with Apache
Ignite" width="555" height="600" />
<h2>What is an In-Memory Data Grid?</h2>
- <p>An in-memory data grid is a read-through/write-through caching
strategy in which the application
- layer treats the data grid as the primary data store. Applications
write to and read
- from the in-memory cluster that propagates all the changes to any
underlying databases automatically keeping them
- updated and consistent with the in-memory data.</p>
-
- <p>Ignite as an in-memory data grid provides all essential APIs needed
to simplify its adoption. The
- APIs include <a href="/use-cases/key-value-store.html">distributed
key-value</a> and <a href="/features/sql.html">ANSI SQL</a> queries, <a
href="/features/acid-transactions.html">ACID transactions</a>, <a
href="/features/collocated-processing.html">co-located processing</a>,
- and <a href="/features/machinelearning.html">machine learning</a>
models. While key-value and SQL calls let you request, join, and group
- distributed data sets, the compute and machine learning components
help to eliminate data
- shuffling over the network, thus, boosting compute and data-intensive
calculations.</p>
-
- <p>Ignite can store data both in memory and on disk with two options
for data persistence. You
- can persist changes in an external database or have Ignite keep data
in its <a href="/arch/native-persistence.html">native persistence</a>. </p>
-
- <h2>IGNITE as an in-memory data grid AND EXTERNAL DATABASES</h2>
+ <p>
+ An in-memory data grid is an advanced read-through/write-through
cache that is deployed on top of multiple databases.
+ The grid supports various APIs, such as SQL, compute, and
key-value. Applications write to and read from the
+ grid, and the grid propagates changes to the underlying data
stores in a consistent way.
+ </p>
+ <p>
+ With Ignite, your applications can utilize multiple APIs for data
processing. Key-value and SQL queries
+ enable you to request, join, and group distributed datasets.
Compute and machine-learning APIs execute
+ logic close to the data, thus eliminating expensive data shuffling
over the network.
+ </p>
- <p>Ignite can improve the performance and scalability of any external
- database such as RDBMS, NoSQL or Hadoop, by sliding in as an
in-memory data grid between the
- application and the database layer. When an application writes
data to the cache, Ignite
- automatically writes-through or writes-behind all data
modifications to the underlying
- external store. Ignite also performs ACID transactions where it
coordinates and commits
- a transaction across the cluster as well as the database.</p>
+ <h2>IGNITE AS AN IN-MEMORY DATA GRID AND EXTERNAL DATABASES</h2>
- <p>Additionally, Ignite can be deployed as a shared and unified
in-memory layer that stores
- data sets originating from disjointed databases. Your applications
can consume all the
- data from Ignite as a single store while Ignite can keep the
original databases in sync
- whenever in-memory data gets updated.</p>
+ <p>
+ Ignite can improve the performance and scalability of most
external databases and data stores (such as RDBMS,
+ NoSQL, and Hadoop) by sliding in as an in-memory data grid
between the application and the database layers.
+ When the application writes data to the cache, Ignite
writes-through or writes-behind all data modifications
+ to the underlying external store. Ignite also performs ACID
transactions (coordinating and committing transactions
+ across both the cluster and the database).
+ </p>
- <p>However, there are some limitations if an external database is used
as a persistence
- layer for Ignite in-memory data grid deployments. For instance, if
you run Ignite SQL
- or scan queries, you need to ensure that all data is preloaded to
the in-memory cluster.
- Note that Ignite SQL or scan queries can read data from disk only
if the data is stored
- in the Ignite native persistence.</p>
+ <p>
+ Additionally, Ignite can be deployed as a shared and unified
in-memory layer that stores datasets that originate
+ from disjointed databases. Your applications can consume all the
data from Ignite as a single store while Ignite
+ synchronizes the original databases whenever in-memory data is
updated.
+ </p>
<h2>IGNITE NATIVE PERSISTENCE</h2>
- <p>Ignite native persistence is a distributed ACID and SQL-compliant
disk store that
- transparently integrates with the Ignite in-memory layer. With
native persistence
- enabled, Ignite stores both data and indexes on disk and
eliminates the time-consuming
- cache warm-up step. The native persistence always keeps a full
copy of data on disk so
- you are free to cache a subset of records in memory. If a required
data record is missing
- in memory, Ignite reads it from the disk automatically regardless
of the API, whether
- you use SQL, key-value, or scan queries.</p>
+ <p>
+ Ignite Native Persistence is a distributed ACID-compliant,
SQL-compliant disk store that transparently
+ integrates with the Ignite in-memory layer. When Native
Persistence is enabled, Ignite stores both
+ data and indexes on disk, thus eliminating the time-consuming
cache warm-up step. Native Persistence
+ keeps a full copy of data on disk, so you are free to cache a
subset of records in memory. If a required
+ data record is missing from memory, Ignite reads the record from
the disk automatically, regardless of the
+ API (whether SQL, key-value, or scan queries).
+ </p>
<div class="jumbotron jumbotron-fluid">
