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From lewi...@apache.org
Subject git commit: GORA-333 - Move README to markdown for better rendering on Github
Date Wed, 04 Jun 2014 15:55:26 GMT
Repository: gora
Updated Branches:
  refs/heads/master e8e58a425 -> a39cfe48e


GORA-333 - Move README to markdown for better rendering on Github


Project: http://git-wip-us.apache.org/repos/asf/gora/repo
Commit: http://git-wip-us.apache.org/repos/asf/gora/commit/a39cfe48
Tree: http://git-wip-us.apache.org/repos/asf/gora/tree/a39cfe48
Diff: http://git-wip-us.apache.org/repos/asf/gora/diff/a39cfe48

Branch: refs/heads/master
Commit: a39cfe48e29aca35e2c0c9d1a7e1a63688b123c4
Parents: e8e58a4
Author: Lewis John McGibbney <lewis.j.mcgibbney@jpl.nasa.gov>
Authored: Wed Jun 4 08:55:14 2014 -0700
Committer: Lewis John McGibbney <lewis.j.mcgibbney@jpl.nasa.gov>
Committed: Wed Jun 4 08:55:14 2014 -0700

----------------------------------------------------------------------
 README.md  | 71 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 README.txt | 72 ---------------------------------------------------------
 2 files changed, 71 insertions(+), 72 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/gora/blob/a39cfe48/README.md
----------------------------------------------------------------------
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..e9021b3
--- /dev/null
+++ b/README.md
@@ -0,0 +1,71 @@
+#Apache Gora Project
+
+<img src="http://gora.apache.org/resources/img/powered-by-gora.png" align="right" width="300"
/>
+ 
+The Apache Gora open source framework provides an in-memory data model 
+and persistence for big data. Gora supports persisting to column stores, 
+key value stores, document stores and RDBMSs, and analyzing the data 
+with extensive Apache Hadoop MapReduce support. 
+
+##Why Gora?
+
+Although there are various excellent ORM frameworks for relational
+databases, data modeling in NoSQL data stores differ profoundly
+from their relational cousins. Moreover, data-model agnostic
+frameworks such as JDO are not sufficient for use cases, where one
+needs to use the full power of the data models in column stores.
+Gora fills this gap by giving the user an easy-to-use ORM framework
+with data store specific mappings and built in Apache Hadoop support.
+
+The overall goal for Gora is to become the standard data representation
+and persistence framework for big data. The roadmap of Gora can be
+grouped as follows.
+
+* Data Persistence : Persisting objects to Column stores such as
+  HBase, Cassandra, Hypertable; key-value stores such as Voldermort,
+  Redis, etc; SQL databases, such as MySQL, HSQLDB, flat files in local
+  file system or Hadoop HDFS.
+
+* Data Access : An easy to use Java-friendly common API for accessing
+  the data regardless of its location.
+
+* Indexing : Persisting objects to Lucene and Solr indexes,
+  accessing/querying the data with Gora API.
+
+* Analysis : Accesing the data and making analysis through adapters for
+  Apache Pig, Apache Hive and Cascading
+
+* MapReduce support : Out-of-the-box and extensive MapReduce (Apache
+  Hadoop) support for data in the data store.
+
+#Background
+
+ORM stands for Object Relation Mapping. It is a technology which
+abstacts the persistency layer (mostly Relational Databases) so
+that plain domain level objects can be used, without the cumbersome
+effort to save/load the data to and from the database. Gora differs
+from current solutions in that:
+
+* Gora is specially focussed at NoSQL data stores, but also has limited
+  support for SQL databases.
+
+* The main use case for Gora is to access/analyze big data using Hadoop.
+
+* Gora uses Avro for bean definition, not byte code enhancement or annotations.
+
+* Object-to-data store mappings are backend specific, so that full data
+  model can be utilized.
+
+* Gora is simple since it ignores complex SQL mappings.
+
+* Gora will support persistence, indexing and anaysis of data, using Pig,
+  Lucene, Hive, etc.
+
+
+ For the latest information about Gora, please visit our website at:
+ 
+   http://gora.apache.org
+ 
+#License
+
+Gora is provided under Apache License version 2.0. See LICENSE.txt for more details.

http://git-wip-us.apache.org/repos/asf/gora/blob/a39cfe48/README.txt
----------------------------------------------------------------------
diff --git a/README.txt b/README.txt
deleted file mode 100644
index 3601089..0000000
--- a/README.txt
+++ /dev/null
@@ -1,72 +0,0 @@
-Apache Gora Project
-===================
- 
-The Apache Gora open source framework provides an in-memory data model 
-and persistence for big data. Gora supports persisting to column stores, 
-key value stores, document stores and RDBMSs, and analyzing the data 
-with extensive Apache Hadoop MapReduce support. 
-
-Why Gora?
----------
-
-Although there are various excellent ORM frameworks for relational
-databases, data modeling in NoSQL data stores differ profoundly
-from their relational cousins. Moreover, data-model agnostic
-frameworks such as JDO are not sufficient for use cases, where one
-needs to use the full power of the data models in column stores.
-Gora fills this gap by giving the user an easy-to-use ORM framework
-with data store specific mappings and built in Apache Hadoop support.
-
-The overall goal for Gora is to become the standard data representation
-and persistence framework for big data. The roadmap of Gora can be
-grouped as follows.
-
-* Data Persistence : Persisting objects to Column stores such as
-  HBase, Cassandra, Hypertable; key-value stores such as Voldermort,
-  Redis, etc; SQL databases, such as MySQL, HSQLDB, flat files in local
-  file system or Hadoop HDFS.
-
-* Data Access : An easy to use Java-friendly common API for accessing
-  the data regardless of its location.
-
-* Indexing : Persisting objects to Lucene and Solr indexes,
-  accessing/querying the data with Gora API.
-
-* Analysis : Accesing the data and making analysis through adapters for
-  Apache Pig, Apache Hive and Cascading
-
-* MapReduce support : Out-of-the-box and extensive MapReduce (Apache
-  Hadoop) support for data in the data store.
-
-Background
-----------
-
-ORM stands for Object Relation Mapping. It is a technology which
-abstacts the persistency layer (mostly Relational Databases) so
-that plain domain level objects can be used, without the cumbersome
-effort to save/load the data to and from the database. Gora differs
-from current solutions in that:
-
-* Gora is specially focussed at NoSQL data stores, but also has limited
-  support for SQL databases.
-
-* The main use case for Gora is to access/analyze big data using Hadoop.
-
-* Gora uses Avro for bean definition, not byte code enhancement or annotations.
-
-* Object-to-data store mappings are backend specific, so that full data
-  model can be utilized.
-
-* Gora is simple since it ignores complex SQL mappings.
-
-* Gora will support persistence, indexing and anaysis of data, using Pig,
-  Lucene, Hive, etc.
-
-
- For the latest information about Gora, please visit our website at:
- 
-   http://gora.apache.org
- 
-License
--------
-Gora is provided under Apache License version 2.0. See LICENSE.txt for more details.


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