![]() Time Series empowers developers to handle this directly within MongoDB with native support for the entire data lifecycle, including storage optimization and performant data analysis. Time series data is common across industries, but can be challenging to work with due to its enormous storage footprint and the difficulty of unlocking real-time insights. MongoDB Time Series is another platform addition that helps developers avoid data silos. Keller Williams has also included a form of fuzzy searching capability that returns results based on incorrect spelling, along with synonyms for search terms. Location-based search is important to users looking for properties, so the company built geolocation features into its Atlas Search-based implementation that change the auto-completion results based on where customers are searching. It implemented auto-completion of user searches for ease of use, and then went one step further. One customer is real estate company Keller Williams, which has been honing its use of Atlas Search to power its customer-facing search experience. Atlas Search provides a full suite of features to help developers deliver search experiences to their users, including autocomplete, fuzzy matching, relevance scoring, geospatial queries, and faceted search, among others. Because it's integrated into the developer data platform, developers can leverage a single query language for both database and search operations. But the developer data platform integrates the database, search engine, and sync mechanism so that developers can build relevance-based search directly into applications.Ītlas Search is based on Apache Lucene, a popular library underpinning several of the most widely used search engines. Previously, many organizations would have defaulted to a separate search engine to address their search needs, and then figured out the plumbing between the systems themselves. Three years ago, MongoDB launched Atlas Search, an embedded full-text search solution in the Atlas multi-cloud database service. It will consolidate organizations' data footprints for example, make their skill sets more adaptable, and generally help them to do more with less.īetter search and support for time series data The data platform should also help companies to consolidate vendors, saving in software licenses and support costs, MongoDB believes. "This has the capability to replace a lot of those disparate data tools" Azam says. But they should also be able to expand the use cases that it caters to and the applications it supports. MongoDB hopes that developers will find this platform familiar and comfortable – after all MongoDB is at the heart of it. At its MongoDB World event last June and over the course of the year, the company has since doubled down with a slew of additional new features. Over the last few years, MongoDB has moved to solve that problem by bringing in not just more of the things that developers have grown to know and love about the database, but also capabilities that they need as their remit expands and stretches - essentially creating a developer data platform.
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