Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Increasingly, applications that deal with big data need to run analytics concurrently with updates. But bridging the gap beten big and fast data is challenging: most of these applications require analytics' results that are fresh and consistent, but without impacting system latency and throughput.  propose virtual lightight snapshots (VLS), a mechanism that enables consistent analytics without blocking incoming updates in NoSQL stores. VLS requires neither native support for database versioning nor a transaction manager. Besides, it is storage-efficient, keeping additional versions of records only when needed to guarantee consistency, and sharing versions across multiple concurrent snapshots.  describe an implementation of VLS in MongoDB and present a detailed experimental evaluation which shows that it supports consistency for analytics with small impact on query evaluation time, update throughput, and latency.
['Fernando Chirigati', 'Jérôme Siméon', 'Martin Hirzel', 'Juliana Freire']
I am writing a research paper on a idea Virtual lightweight snapshots for consistent analytics in NoSQL stores
[{"from": "human", "value": "I am writing a research paper on a idea Virtual lightweight snapshots for consistent analytics in NoSQL stores"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Increasingly, applications that deal with big data need to run analytics concurrently with updates. But bridging the gap beten big and fast data is challenging: most of these applications require analytics' results that are fresh and consistent, but without impacting system latency and throughput.  propose virtual lightight snapshots (VLS), a mechanism that enables consistent analytics without blocking incoming updates in NoSQL stores. VLS requires neither native support for database versioning nor a transaction manager. Besides, it is storage-efficient, keeping additional versions of records only when needed to guarantee consistency, and sharing versions across multiple concurrent snapshots.  describe an implementation of VLS in MongoDB and present a detailed experimental evaluation which shows that it supports consistency for analytics with small impact on query evaluation time, update throughput, and latency."}]