As data proliferates, whether through the Internet of Things, real time analytics or web-based applications, the need for an open-source based backend to support real time access to truly big data is becoming a must. While everyone accepts that most IoT and future big data deployments will use open source technology, there exists a wide universe of open source elements that can be connected to serve as a backend for big data, offering a persistence layer and being able to scale well. We will discuss the advantages and disadvantages of using SQL over NoSQL datastores, optimal solutions to the Blob problems, what “real-time” really means, dealing with sharding, spatial data types and the expected throughputs of such systems and more. We’ll examine the pros and cons of using backends made of Crate, MongoDB, Elasticsearch, GridFS, Hadoop, Riak, Solr, Rados CouchDB and others.
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