6 Big Reasons to Upgrade to MongoDB 6.0

Posted By :Sakshat Singhal |29th July 2022

MongoDB 6.0, which was first introduced at MongoDB World 2022, is now generally accessible and ready for download. The new features in MongoDB 6.0 complement those in the earlier 5.1–5.3 Rapid Releases and help you handle more use cases, increase operational resilience at scale, and secure and protect your data.

Simplification is a recurring theme in MongoDB 6.0; rather than requiring you to use external software or third-party tools, these new MongoDB capabilities let you design, iterate, test, and publish apps more quickly.

The most recent release aids developers in preventing data silos, perplexing architectures, time wasted integrating third-party technology, missed SLAs and other possibilities, and consequently the requirement for bespoke work (such as pipelines for exporting data).


This is what to anticipate from MongoDB 6.0.

1. Added assistance for using statistical data

Statistical data is essential for contemporary applications and is used in everything from financial services to e-commerce. When properly gathered, processed, and evaluated, statistical data can reveal a wealth of information that can help you expand your business and enhance your application, from user growth to potential revenue streams.

Statistic collections, which were first made available in MongoDB 5.0, offer a solution to manage these workloads without having to rely on specialized technology and the associated complexity.

Additionally, it was crucial to get through challenges particular to time series data, such as high volume, storage and cost issues, and gaps in data continuity (caused by sensor outages).

Since their debut, statistic collections have undergone a series of swift releases that have been used to update and improve them. We started by introducing sharding for statistical collections 

(5.1) to increase data distribution, followed by the implementation of columnar compression (5.2) to improve storage footprints, and finally, the introduction of densification and gap-filling (5.3) to enable teams to perform statistical analyses even when some data points are missing.

With the addition of secondary and compound indexes on measures in version 6.0, statistical collections now offer better read speed and new use cases like geo-indexing. Developers can expand and broaden the analysis to include scenarios involving distance and location by tying geographic information to statistical data. This may be done by tracking temperature changes in refrigerated delivery vans on a hot summer day or by keeping an eye on the amount of fuel that cargo ships use on particular routes.

Additionally, we have enhanced type operations and query performance.

For speedier reads, MongoDB, for example, can now easily return the latest datum in a series rather than scanning the entire collection.

To sort time and metadata fields effectively, you'll also employ clustered and secondary indexes.


2. An improved method for creating event-driven structures

Users now anticipate real-time, event-driven experiences like activity feeds, notifications, and recommendation engines thanks to the introduction of apps like Seamless and Uber. However, it is difficult to move at the speed of the crucial world because your application must immediately recognize and respond to changes in your data.

Change streams, which were first introduced in MongoDB 3.6, offer an API for streaming any changes to a MongoDB database, cluster, or collection without the significant overhead associated with having to poll your entire system. Your application will then be able to respond automatically, such as by producing an in-app notification to inform you that your delivery has left the warehouse or by setting up a pipeline to index new logs as they are produced.


With the addition of new capabilities, the MongoDB 6.0 release enhances change streams and advances them. You may send updated versions of complete documents downstream, reference deleted documents, and more now that you can see the before and after states of a document that has been altered. Additionally, data definition language (DDL) activities like adding or removing collections and indexes are now supported by change streams.

Additionally, $lookup's performance has been improved. As an illustration, $lookup can provide results between 5 and 10 times faster than before if there is an index on the foreign key and a modest number of documents have been matched. $lookup will be twice as quick as earlier iterations if a larger number of documents match. If no indexes are available (and the join is being used for exploratory or ad hoc queries), $lookup will result in a 100-fold performance gain.

Your applications can now run complicated analytical queries against a globally and transactionally consistent snapshot of your real-time, operational data thanks to the introduction of read concern snapshot and the resulting optional atClusterTime parameter. MongoDB will maintain point-in-time consistency of the query results delivered to your users even when the data beneath you changes.

These point-in-time analytical queries with big distributed datasets can span numerous shards. By sending these queries to secondaries, you may avoid lengthy, brittle, and expensive ETL to data warehouses and separate analytical workloads from transactional workloads with both being handled by the same cluster. Visit our documentation to learn more.


3. Less work with more operators

Increase your output using a selection of the newest operators, which can help you do more work in the database while spending less time manually manipulating data or creating code. Long stretches of code and key commands will be automated by these new MongoDB operators, freeing up more developer time to specialize in other duties.

For instance, operators like $maxN, $minN, or $lastN make it simple to find significant values in your data set. Additionally, you'll sort array components directly in your aggregate pipelines using an operator like $sortArray.


4. More durable business practices

Users are empowered to confront and overcome outages thanks to MongoDB's replica set design from the outset.

Initial sync, which is essential for catching up with nodes that have fallen behind or when adding additional nodes to improve resilience, read scalability, or query latency, is the process by which a reproduction set member in MongoDB loads a full copy of data from an existing member.

Initial sync via file copy is a feature of MongoDB 6.0 that is up to four times faster than previous, standard approaches. MongoDB Enterprise Server offers this capability.

Along with the work on initial sync sharding, the technology that enables horizontal scalability, receives significant upgrades in MongoDB 6.0. Now that sharded collections have a default chunk size of 128 MB, there will be fewer chunk migrations and better networking and internal overhead performance at the query routing layer. a substitute configures Collection A collection may be defragmented using the balancing command to lessen the effect of the sharding balancer.


5. Enhanced operational effectiveness and data security

New capabilities in MongoDB 6.0 remove the need to choose between safe data and effective operations.

Client-side field-level encryption (CSFLE), which became generally available in 2019, has aided numerous enterprises in managing sensitive data with confidence, particularly as they shift more of their application estate into the general public cloud. CSFLE will support any KMIP-compliant key management provider with MongoDB 6.0. As the leading industry standard, KMIP simplifies the processing, modification, and storage of cryptographic objects like certificates, encryption keys, and more.


In installations with numerous users, MongoDB's capability for auditing enables administrators to track system behavior, assuring accountability for database-wide operations. While auditors must have access to audit logs to evaluate operations, the information contained in audit logs must be kept secure from unauthorized individuals because it may be sensitive.

In MongoDB 6.0, administrators can use their own KMIP-compliant key management system to compress and encrypt audit events before they are written to the disc. The confidentiality and integrity of the occurrences will be safeguarded by encrypting the logs. The logs remain encrypted if they pass through any central log management systems or SIEM.

6. Improved search performance and seamless data synchronization

In addition to the 6.0 Major Release, MongoDB will make supplementary features generally accessible and preview-ready.

The first is Atlas Search facets, which provide quick results filtering and counting so that users can quickly focus their searches and find the information they require. The capability for sharded collections will be added to facets when they are released in preview at MongoDB World 2022.

Cluster-to-Cluster Sync is another significant update that enables you to easily migrate data to the cloud, spin up development, test, or analytics environments, and support compliance standards and audits.


Cluster-to-Cluster Sync synchronizes two MongoDB clusters' data continuously and unidirectionally in any context, including hybrid, Atlas, on-premises, and the edge. Additionally, you will have real-time control over the synchronization process, which you may start, stop, resume, or even reverse as necessary.

In the end, MongoDB 6.0's new features are meant to simplify operations and development, break down data silos, and get rid of the complexity that comes with the needless employment of different specialty technologies. That implies more time for idea generation and building and less time for custom work, debugging, and perplexing architectures.

About Author

Sakshat Singhal

Sakshat Singhal possesses a diverse set of skills as a QA Engineer with years of hands-on experience in various testing methodologies, including Manual Testing, Non-Functional Testing like Database Testing, API Testing, Load Testing, and Performance Testing. He is proficient in using databases like SQL, MongoDB, and more. Sakshat has played a pivotal role in ensuring the success of client projects, including Konfer Vis360, by delivering high-quality work and leveraging his knowledge of the latest technologies. With his analytical skills, he can effectively analyze complex systems and identify potential issues and solutions, contributing to the successful delivery of client projects.

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