This is an automated email from the ASF dual-hosted git repository.

namelchev pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/ignite-extensions.git


The following commit(s) were added to refs/heads/master by this push:
     new 63815eb  IGNITE-14942 Fixes README description. (#65)
63815eb is described below

commit 63815eb70b508dff955dcf224d9dd42b785b800e
Author: Mikhail Petrov <32207922+ololo3...@users.noreply.github.com>
AuthorDate: Fri Jun 25 08:57:41 2021 +0300

    IGNITE-14942 Fixes README description. (#65)
---
 README.md | 48 ++++++------------------------------------------
 1 file changed, 6 insertions(+), 42 deletions(-)

diff --git a/README.md b/README.md
index 226a0e0..888b30f 100644
--- a/README.md
+++ b/README.md
@@ -2,53 +2,17 @@
 
 <a href="https://ignite.apache.org/";><img 
src="https://github.com/apache/ignite-website/blob/master/images/ignite_logo_full.svg";
 hspace="20"/></a>
 
-[![Build 
Status](https://travis-ci.org/apache/ignite.svg?branch=master)](https://travis-ci.org/apache/ignite)
 
[![GitHub](https://img.shields.io/github/license/apache/ignite?color=blue)](https://www.apache.org/licenses/LICENSE-2.0.html)
-[![Maven 
Central](https://maven-badges.herokuapp.com/maven-central/org.apache.ignite/ignite-core/badge.svg)](https://search.maven.org/search?q=org.apache.ignite)
-[![GitHub 
release](https://img.shields.io/badge/release-download-brightgreen.svg)](https://ignite.apache.org/download.cgi)
-![GitHub commit 
activity](https://img.shields.io/github/commit-activity/m/apache/ignite)
+[![GitHub 
release](https://img.shields.io/badge/release-download-brightgreen.svg)](https://ignite.apache.org/download.cgi#extensions)
 [![Twitter 
Follow](https://img.shields.io/twitter/follow/ApacheIgnite?style=social)](https://twitter.com/ApacheIgnite)
 
-## What is Apache Ignite?
+## What Are Apache Ignite Extensions?
 
-Apache Ignite is a distributed database for high-performance computing with 
in-memory speed.
+Apache Ignite Extensions is a group of integrations between [Apache 
Ignite](https://ignite.apache.org) and various Java frameworks.  
+To see the comprehensive list of Apache Ignite Extensions and related 
documentation, visit the *"Extensions and Integrations"* section of an  [Apache 
Ignite Documentation](https://ignite.apache.org/docs/latest/). 
 
-<p align="center">
-    <a href="https://ignite.apache.org";>
-        <img 
src="https://github.com/apache/ignite-website/blob/master/images/png-diagrams/ignite_cluster.png";
 width="400px"/>
-    </a>
-</p>
+## Apache Ignite Extensions Publication And Versioning.
 
-* [Technical Documentation](https://ignite.apache.org/docs/latest/)
-* [JavaDoc](https://ignite.apache.org/releases/latest/javadoc/)
-* [C#/.NET APIs](https://ignite.apache.org/releases/latest/dotnetdoc/api/)
-* [C++ APIs](https://ignite.apache.org/releases/latest/cppdoc/)
-* [Scala 
APIs](https://ignite.apache.org/releases/latest/scaladoc/scalar/index.html)
+Each Apache Ignite extension is published as a separate Maven artifact and has 
an independent release lifecycle. Visit the *"Extensions and Integrations"* 
section of an  [Apache Ignite 
Documentation](https://ignite.apache.org/docs/latest/) to see Maven Artifact ID 
and available versions for each extension, as well as the corresponding Apache 
Ignite and extension target compatible versions.
 
-## Multi-Tier Storage
-
-Apache Ignite is designed to work with memory, disk, and Intel Optane as 
active storage tiers. The memory tier allows using DRAM and IntelĀ® Optaneā„¢ 
operating in the Memory Mode for data storage and processing needs. The disk 
tier is optional with the support of two options -- you can persist data in an 
external database or keep it in the Ignite native persistence. SSD, Flash, HDD, 
or Intel Optane operating in the AppDirect Mode can be used as a storage device.
-
-[Read More](https://ignite.apache.org/arch/multi-tier-storage.html)
-
-## Ignite Native Persistence
-
-Even though Apache Ignite is broadly used as a caching layer on top of 
external databases, it comes with its native persistence - a distributed, ACID, 
and SQL-compliant disk-based store. The native persistence integrates into the 
Ignite multi-tier storage as a disk tier that can be turned on to let Ignite 
store more data on disk than it can cache in memory and to enable fast cluster 
restarts.
-
-[Read More](https://ignite.apache.org/arch/persistence.html)
-
-## ACID Compliance
-Data stored in Ignite is ACID-compliant both in memory and on disk, making 
Ignite a **strongly consistent** system. Ignite transactions work across the 
network and can span multiple servers.
-
-[Read More](https://ignite.apache.org/features/transactions.html)
-
-## ANSI SQL Support
-Apache Ignite comes with a ANSI-99 compliant, horizontally scalable, and 
fault-tolerant SQL engine that allows you to interact with Ignite as with a 
regular SQL database using JDBC, ODBC drivers, or native SQL APIs available for 
Java, C#, C++, Python, and other programming languages. Ignite supports all DML 
commands, including SELECT, UPDATE, INSERT, and DELETE queries as well as a 
subset of DDL commands relevant for distributed systems.
-
-[Read More](https://ignite.apache.org/features/sql.html)
-
-## Machine Learning and High-Performance Computing
-[Apache Ignite Machine 
Learning](https://ignite.apache.org/features/machinelearning.html) is a set of 
simple, scalable, and efficient tools that allow building predictive machine 
learning models without costly data transfers. The rationale for adding machine 
and deep learning to Apache Ignite is quite simple. Today's data scientists 
have to deal with two major factors that keep ML from mainstream adoption.
-
-High-performance computing (HPC) is the ability to process data and perform 
complex calculations at high speeds. Using Apache Ignite as a [high-performance 
compute cluster](https://ignite.apache.org/use-cases/hpc.html), you can turn a 
group of commodity machines or a cloud environment into a distributed 
supercomputer of interconnected Ignite nodes. Ignite enables speed and scale by 
processing records in memory and reducing network utilization with APIs for 
data and compute-intensive calc [...]
 

Reply via email to