Used mostly in applications related to the Internet of Things(IoT), Mobile, Cloud Computing, etc. Used mostly in applications related to search, security, metrics, maps, logging, etc. Since there is no inbuilt web interface, third-party applications can be used to retrieve data that is not always secure hence, it is not entirely reliable.ĭata retrievals are reliable due to the web interface. Known to lose data during write operations Write operations are reliable and accurate. Lucene, therefore, unlimited indexing already index data. Indexing is limited here due to storage constraints. It does not support Mapreduce operations on huge data but runs text search filter on huge data. Kibana is a visualization tool used to visualize the logs to understand the operations.Īllows Mapreduce operations on the data to manage high scale data Queries and sometimes modifies the existing hosted data as it is just a search engine wrapper.Ĭompass, a GUI to visualize MongoDB data, mongo shell is also present for the command-line interface. Most probable matches for the given queriesĭocuments are stored in BSON format (Binary JSON). to match to the most likely results.Įxact matches for query filters are returned. Uses Vector space model, Information Retrieval etc. It is a distributive search Engine wrapper on Lucene library.ĭata is retrieved by comparing documents. It is a relational general-purpose database. Multiple instances of the same data can be created, and various operations can be done on the data the instances hold.Ĭomparison between MongoDB and Elasticsearchīelow are the top 10 comparisons between MongoDB and Elasticsearch: MongoDB
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