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NoSQL: Emerging Trends and Innovations

| by Srini Penchikala on Jan 28, 2014 |

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NoSQL databases have been getting lot of attention over the last few years. There are several trends and innovations happening in this space. InfoQ would like to learn what new trends in NoSQL databases you are currently using or planning on using in the future.

 

Multi-model Databases:

These databases offer flexible data models for storing different type of data structures like Documents, Graphs, and Key-value type data sets. Some of these databases also support SQL-like query language or JavaScript extensions.

Examples:

NewSQL:

NewSQL databases support ACID transactions compliance and scalability.

Examples:

Time Series Databases:

Time series databases are optimized for the storage, retrieval, and analysis of time series data generated from sources like sensors, smart meters, and servers. Time series databases are seeing the re-emergence in the usage of time series data.

Examples:

  • kairosdb: A rewrite of the original OpenTSDB project started at Stumble Upon. Written primarily for Cassandra but works with HBase as well.
  • opentsdb: Written on top of Apache HBase.
  • tempo-db: This is a cloud based solution. Supports REST API interface.
  • SciDB: SciDB database, called a Data Management and Analytics Software System (DMAS), is optimized for data management of big data and analytics. Data storage is write once, read many, based on bulk loads, rather than single row inserts. Complex analytics are simplified because arrays and vectors are first class objects with built in optimized operations. Spatial operators and time series analysis are easy to express.

Database as a service:

Database as a service is basically cloud-based data management. These databases offer a web service interface to manage the database running on the cloud.

Examples:

 

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