MongoDB, provider of a general purpose database platform, has added products to give developers a better way to work with data—wherever it resides. According to the company, the launch of MongoDB 4.4, general availability of Atlas Data Lake and Atlas Search, and the general availability of MongoDB Realm offer organizations an escape from data silos and fragmented APIs as MongoDB Cloud delivers a developer-optimized, cloud-to-mobile platform.
“Developers today are expected to leverage a myriad of technologies, data models, APIs and languages across disparate systems in order to support the transactional, search and analytical features that users demand in modern applications. And while cloud computing has revolutionized the tech industry, providing a low cost of entry and unlimited scale among other proven benefits, most cloud migrations have merely replicated the complexities and drawbacks of the traditional data center,” said Dev Ittycheria, president & CEO of MongoDB. “With MongoDB Cloud, developers can finally leave the burden of data silos and sprawl behind and truly unlock the value of data through a unified development experience.”
With MongoDB’s document data model, developers can structure data any way the application requires—from rich, hierarchical objects to simple key-value pairs and tables to connected graphs—and then query it with a single API. The announcement of MongoDB 4.4 furthers the company’s objective of continuing to provide developers with a modern general purpose database. MongoDB 4.4 delivers the features and enhancements most demanded by the MongoDB community. The result is a database designed to enable users to build transactional, operational and analytical applications faster and more efficiently than any other database. MongoDB 4.4 allows developers to scale applications globally, with the flexibility to define and refine the distribution of data at any time as requirements evolve while delivering the most sophisticated latency, resilience and security controls anywhere in the cloud.
Notable new features in 4.4 include:
- Union: Empowers users with richer and faster analytics to make better decisions while reducing dependencies on fragile ETL processes and expensive data warehouses
- Refinable shard keys: Allows for easier scale-out of MongoDB, with the ability to modify the locations of data at any time as applications and business requirements evolve
- Hedged reads: Delivers consistent and predictable performance—even when some nodes might not be working optimally—by submitting read requests to multiple replicas and returning results to the client as soon as the quickest node responds
Atlas Data Lake and Atlas Search
The addition of Atlas Data Lake and Atlas Search to the MongoDB Cloud platform is aimed at simplifying modern data infrastructure, extending applications with rich search experiences and unlocking the power of analytics for data archived in a data lake. Using the MongoDB Query Language (MQL) and data model, Atlas Data Lake a user can run a query and have the data brought back to them: whether it is real-time transactional data in the global Atlas global cloud database or a relevance-based search query with Atlas Search or a long-running analytical query on data in object storage. Using MongoDB Cloud, developers no longer need to deal with the cognitive burden of flipping back and forth between multiple technologies, query languages and data models.
Atlas Data Lake allows users to connect to their existing S3 storage buckets with a few clicks from the MongoDB Atlas UI in order to run queries and explore their data using the power of MQL. Atlas Data Lake is also completely serverless, so there is no infrastructure to set up, manage or optimize, and customers pay only for the queries they run when actively working with the data.
With Atlas Data Lake allows users to
- Use Atlas Online Archive: Data is tiered across fully managed databases and cloud object storage, with the ability to query the data seamlessly via a single query. By automatically archiving historical data, customers save on transactional database storage costs while still being able to easily query that data
- Do federated queries: Eliminates the cost and complexity of moving and transforming data by enabling users to run a single query across Atlas and historical data on Amazon S3, returning a single result
- Persist aggregations to Amazon S3 & Atlas: Provides users greater flexibility to persist results of complex aggregations to their preferred storage tier, exposing new data-driven insights for real-time applications in a cost-effective manner
Atlas Search is integrated with the Atlas cloud database with a consistent API so users do not need to spin up a separate search engine and synchronize data movement between different data silos. Once indexes have been created using either the Atlas UI or API, developers can run sophisticated search queries using MQL, saving significant effort, time and money.
Building on its 2019 acquisition of the popular open source mobile database and synchronization platform, Realm.io, to help developers build rich, mobile applications more quickly, MongoDB has announced that MongoDB Realm, now generally available, integrates with MongoDB’s serverless platform to give developers a uniform and easier way to work with data all the way through the application lifecycle – from the front to the backend.
An example of what can be achieved withMongoDB Realm is the new feature, Realm Sync, which enables bi-directional data synchronization between Realm’s mobile client on the front end and Atlas on the backend. This allows for data to be seamlessly shared between devices and with the backing database without complex conflict resolution and integration code.
For more information, go to www.mongodb.com.