Yesterday, the team at MongoDB announced new cloud services and features that will offer a better way to work with data. The beta versions of MongoDB Atlas Data Lake and MongoDB Atlas Full-Text Search will help users to access new features in a fully managed MongoDB environment.
The general availability of MongoDB Charts will help customers in creating charts and graphs, and further building and sharing dashboards. It also helps in embedding these charts, graphs and dashboards directly into web apps for creating better user experiences.
MongoDB Charts is generally available to Atlas as well as on-premise customers which help in creating real-time visualization of MongoDB data.
The MongoDB Charts include new features, such as embedded charts in external web applications, geospatial data visualization with new map charts, and built-in workload isolation for eliminating the impact of analytics queries on an operational application.
Dev Ittycheria, CEO and President, MongoDB, said, “Our new offerings radically expand the ways developers can use MongoDB to better work with data.”
He further added, “We strive to help developers be more productive and remove infrastructure headaches — with additional features along with adjunct capabilities like full-text search and data lake. IDC predicts that by 2025 global data will reach 175 Zettabytes and 49% of it will reside in the public cloud. It’s our mission to give developers better ways to work with data wherever it resides, including in public and private clouds.”
MongoDB Atlas Data Lake helps customers to quickly query data on S3 in any format such as BSON, CSV, JSON, TSV, Parquet and Avro with the help of MongoDB Query Language (MQL).
One of the major plus points about MongoDB Query Language is that it is expressive and will that allows developers to query the data. Developers can now use the same query language across data on S3, and make querying massive data sets easy and cost-effective.
With MQL being added to MongoDB Atlas Data Lake, users can now run queries and explore their data by giving access to existing S3 storage buckets with a few clicks from the MongoDB Atlas console.
Since the Atlas Data Lake is completely serverless, there is no need for setting up an infrastructure or managing it. Also, the customers pay only for the queries they run when they are actively working with the data. The team has planned for the availability of MongoDB Atlas Data Lake on Google Cloud Storage and Azure Storage for the future.
Atlas Full-Text Search offers rich text search capabilities that are based on Apache Lucene 8 against fully managed MongoDB databases. Also, there is no need for additional infrastructure or systems to manage. Full-Text Search helps the end users in filtering, ranking, and sorting their data for bringing out the most relevant results. So, users are not required to pair their database with an external search engine
To know more about this news, check out the official press release.
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