Apache Gora description
An ORM framework for column stores
It supports environments such as Apache HBase, Apache Cassandra and a specific focus on Hadoop.
Here are some key features of "Apache Gora":
- 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 of 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 - Accessing 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.
- Gora is specially focused 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 analysis of data, using Pig, Lucene, Hive, etc.
- Large improvements within the gora-cassandra module including a number of bug fixes, significant upgrades to Apache Cassandra and Hector Client API usage and a number of improvements to the gora-core API.