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jnosql-diana-driver's Introduction

Diana Project

Diana Driver

Diana is a flexible and extensible API to connect NoSQL databases. It brings an easy interface to support key-value, column family, document oriented and graph databases as JDBC does for SQL databases. This project has several drivers to Diana API.

  • Arangodb: ArangoDB is a native multi-model database with flexible data models for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.
  • Cassandra: Apache Cassandra is a free and open-source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.
  • Couchbase: Couchbase Server, originally known as Membase, is an open-source, distributed multi-model NoSQL document-oriented database software package that is optimized for interactive applications.
  • Elasticsearch: Elasticsearch is a search engine based on Lucene. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. Elasticsearch is developed in Java and is released as open source under the terms of the Apache License. Elasticsearch is the most popular enterprise search engine followed by Apache Solr, also based on Lucene.
  • Hazelcast:In computing, Hazelcast is an open source in-memory data grid based on Java.
  • Hbase: HBase is an open source, non-relational, distributed database modeled after Google's BigTable and is written in Java. It is developed as part of Apache Software Foundation's Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System), providing BigTable-like capabilities for Hadoop. That is, it provides a fault-tolerant way of storing large quantities of sparse data (small amounts of information caught within a large collection of empty or unimportant data, such as finding the 50 largest items in a group of 2 billion records, or finding the non-zero items representing less than 0.1% of a huge collection).
  • Mongodb: MongoDB is a free and open-source cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with schemas.
  • Orientdb: OrientDB is an open source NoSQL database management system written in Java. It is a multi-model database, supporting graph, document, key/value, and object models, but the relationships are managed as in graph databases with direct connections between records. It supports schema-less, schema-full and schema-mixed modes. It has a strong security profiling system based on users and roles and supports querying with Gremlin along with SQL extended for graph traversal. OrientDB uses several indexing mechanisms based on B-tree and Extendible hashing, the last one is known as "hash index", there are plans to implement LSM-tree and Fractal tree index based indexes. Each record has Surrogate key which indicates position of record inside of Array list , links between records are stored either as single value of record's position stored inside of referrer or as B-tree of record positions (so-called record IDs or RIDs) which allows fast traversal (with O(1) complexity) of one-to-many relationships and fast addition/removal of new links. OrientDB is the second most popular graph database according to the DB-Engines graph database ranking
  • Redis: Redis is a software project that implements data structure servers. It is open-source, networked, in-memory, and stores keys with optional durability.
  • Riak: Riak (pronounced "ree-ack" ) is a distributed NoSQL key-value data store that offers high availability, fault tolerance, operational simplicity, and scalability. In addition to the open-source version, it comes in a supported enterprise version and a cloud storage version. Riak implements the principles from Amazon's Dynamo paper with heavy influence from the CAP Theorem. Written in Erlang, Riak has fault tolerance data replication and automatic data distribution across the cluster for performance and resilience.

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