UPDATED 09:00 EDT / JULY 13 2021

BIG DATA

MongoDB 5.0 release adds time-series data and serverless instances into the mix

MongoDB Inc. is updating its namesake document-oriented database, adding key enhancements such as time series support and a preview of serverless database in the cloud version of its platform.

In addition to the MongoDB 5.0 release, the company announced some major enhancements to Atlas Data Lake, Atlas Search and MongoDB Realm during its MongoDB.live event today.

The open-source MongoDB database is incredibly popular, used to power thousands of big data applications and other data-hungry workloads. MongoDB is what’s called a “multimodal database” that can handle many different types of applications and store data in many kinds of formats. That’s handy for developers, because it means they only need to use a single query language and one consistent application programming interface to build their apps with.

MongoDB is most often used to power analytical and transactional applications for healthcare, financial services, insurance and telecommunications providers.

MongoDB 5.0 becomes a lot more flexible thanks to its native support for time series data, which refers to a series of data points that are indexed, listed or graphed in time order. Those data points could be server metrics, application performance monitoring, network data, sensor data, events, clicks, trades in a market or any other kind of analytics data. The idea is that it helps users to query metrics and events or measurements that are time-stamped, at much faster speeds than is possible with databases that aren’t time-series.

“Designed for IoT and financial analytics, our new time series collections, clustered indexing, and window functions make it easier, faster and lower-cost to build and run time series applications, and to enrich your enterprise data with time series measurements,” MongoDB Chief Technology Officer Mark Porter said in a blog post.

Developers will be glad to know that MongoDB is helping them to future-proof their applications too. The new Versioned API makes it possible to upgrade to each new MongoDB release without any risk of “backward-breaking changes” that require them to refactor their apps.

“Using the new versioned API decouples your app lifecycle from the database lifecycle, so you only need to update your application when you want to introduce new functionality, not when you upgrade the database,” Porter explained.

Constellation Research Inc. analyst Holger Mueller told SiliconANGLE the versioned API is perhaps one of the most important of today’s updates, noting “they have become key for allowing customers to move their applications at their own pace.”

That’s not all. There’s also a new function called Live Resharding, which according to Porter makes it easy for users to shard their databases on demand, with no downtime.

Sharding is a method of splitting and storing a single logical data set in multiple databases. By distributing the data among multiple machines, a cluster of database systems can store larger data set and handle additional requests. Sharding therefore allows a database cluster to scale along with its data and traffic growth.

“The way I like to think about this is that we’ve extended the flexibility the document model has always given you down to how you distribute your data,” Porter explained. “So as things change, MongoDB instantly adapts without expensive schema or sharding migrations.”

A more interesting and perhaps riskier update is the redesigned MongoDB Shell, which is the interactive JavaScript interface that’s used to access MongoDB. Porter said the new Shell has been rebuilt from the ground up to offer a more modern command-line experience, with enhanced usability features and a more powerful scripting environment.

“It makes it even easier for users to interact and manage their MongoDB data platform, from running simple queries to scripting admin operations,” Porter said.

Mueller said MongoDB is making a big push with a breathless list of impressive updates, but he said it’s taking a risk with the redesigned shell. “Developers don’t generally like their living room to be rearranged by a vendor too often,” he said. “We’ll have to wait and see how popular these changes are.”

MongoDB Atlas get serverless instances and more

Those who use the cloud-based MongoDB Atlas managed service have something that’s potentially even more exciting, with the availability of serverless instances now in preview.

Serverless is a model that enables developers to build and run their apps without having to manage the underlying infrastructure, so they can devote more of their time writing code.

By bringing serverless instances to MongoDB Atlas, the company is giving developers an easier way to ensure that their database workloads will always have access to the infrastructure resources they need.

Serverless is really just about making things simple, Porter explained. With MongoDB Atlas serverless instances, the only thing developers need to choose is which cloud region they want their data to be hosted in. Once that choice is made, they’ll be able to access an on-demand database endpoint that can dynamically adapt to their application traffic, he said.

“Serverless instances will support the latest MongoDB 5.0 GA release, Versioned API, and upcoming Rapid Releases so you never have to worry about backwards compatibility or upgrades,” Porter added. “Pay only for reads and writes your application performs and the storage resources you use (up to 1TB of storage in preview) and leave capacity management to MongoDB Atlas’s best-in-class automation.”

The enhancements continue with Atlas Data Lake, a self-service application in MongoDB Atlas that allows users to natively query, transform and move data across Amazon Web Services S3 and MongoDB Atlas clusters. Today’s update integrates MongoDB Charts with Atlas Data Lake, making it easier to visualize data stored in MongoDB Atlas and Amazon S3 without moving or transforming it first.

Atlas Search is improved with a new Function Scoring capability that allows users to apply mathematical formulas on fields within documents that can influence their relevance, such as popularity or distance. The same capability also makes it possible to define collections of synonyms for a particular search index. By associating similar terms with each other, users can respond to a wider range of user-initiated queries in applications.

Finally, there’s a small update to MongoDB Realm, which is a serverless version of the MongoDB database that’s designed to power mobile applications. Realm now supports the Unity game engine, which means it can be used to store game data such as player’s scores and stats and sync that information across devices.

Image: MongoDB

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