MongoDB versions and storage engines

This version is phrased out. For more information, see Notice: ApsaraDB for MongoDB has phased MongoDB 3.2 out and released MongoDB 4.2 since February 4.

MongoDB 5.0 natively supports the entire lifecycle of time series data, from ingestion, storage, query, real-time analysis, and visualization through to online archival or automatic expiration as data ages. This makes it faster to build and run time series applications at a lower cost. With the release of MongoDB 5.0, MongoDB has expanded the universal application data platform, which makes it easier for developers to process time series data. This further expands the use scenarios of MongoDB in areas such as IoT, financial analysis, and logistics.

The Versioned API allows new features and improvements to be flexibly added to the database of each version with full backward compatibility. When you want to change an API, you can add a new version of the API and run it on the same server at the same time as the existing version of the API. With the accelerated release of MongoDB versions, the Versioned API enables quicker and easier access to the features of the latest MongoDB version.

The Versioned API defines a set of commands and parameters that are most commonly used in applications. These commands do not change regardless of whether a database release is an annual major release or a quarterly rapid release. You can pin the driver to a specific version of the MongoDB API by decoupling the application lifecycle from the database lifecycle. This way, even if the database is upgraded and improved, your application can continue to run for several years without modifications to code.

Starting with MongoDB 5.0, the default write concern is majority. A write operation is committed and write success is passed back to the application only when the write operation is applied to the primary node and persisted to the logs of a majority of secondary nodes. This ensures that MongoDB 5.0 can provide stronger data durability guarantees out of the box.

Long-running snapshot queries improve the versatility and flexibility of applications. By default, snapshot queries executed by this feature have an execution duration of 5 minutes. You can also customize the duration of a snapshot query. In addition, this feature maintains strong consistency with snapshot isolation guarantees without impacting the performance of your live and transactional workloads, and enables snapshot queries to be executed on secondary nodes. This allows you to run different workloads in a single cluster and scale your workloads to different shards.

For enhanced user experience, the new MongoDB Shell has been redesigned from the ground up to provide a modern command-line experience, enhanced usability features, and a powerful scripting environment. The new MongoDB Shell has become the default shell for MongoDB. The new MongoDB Shell introduces syntax highlighting, intelligent auto-complete, contextual help, and useful error messages to create an intuitive and interactive experience.

Starting with the 5.0 release, MongoDB is released as two different release series: Rapid Releases and Major Releases. Rapid Releases are available for evaluation and development purposes. We recommend that you do not use Rapid Releases in a production environment.

Existing indexes are hidden to ensure that these indexes are not used in subsequent queries. You can check whether the deletion of a specified inefficient index compromises performance. If not, you can delete the inefficient index.

One or more suffix fields are added to improve the distribution of existing documents on chunks. This prevents concurrent access to a single shard and alleviates pressure on servers.

A single hash field can be specified in a composite index to simplify the business logic.

For sharded clusters, a read request can be simultaneously sent to two replicas of the same shard. The results first received are used to recover the client. This reduces the request latency.

Operation logs of the primary database actively flow into the secondary database. Compared with the previous version where the secondary database is polled, this method saves nearly half of the round-trip time and improves the performance of data replication between the primary and secondary databases.

The indexing processes of the primary and secondary databases are synchronized. This greatly reduces the latency generated by the primary and secondary databases in the indexing processes and ensures that the secondary database can access the most recent data in a timely manner.

The primary node synchronizes a portion of read traffic to the secondary node for processing. The secondary node processes read traffic, which can reduce the access latency.

MongoDB supports resumable upload during full synchronization between primary and secondary nodes. This prevents the need for a full synchronization from scratch in the event of a network disconnection.

You can customize the retention period of operation logs. When operation logs are cleared, full synchronization from the primary node is required.

The $unionWith stage is added to improve the query performance of MongoDB. This stage is similar to the UNION ALL statement in SQL.

The $accumulator and $function operators are added to implement custom aggregation expressions and improve interface consistency and user experience.

The two-phase commit method ensures the ACID feature of sharded cluster transactions, expands business scenarios, and achieves a leap from NoSQL to NewSQL.

The repeatable read feature provides the automatic retry capability in a poor-quality network environment. This reduces logic complexity on the service side and ensures continuity of your business.

You can create a wildcard index for nondeterministic fields to overwrite multiple feature fields in a document for flexible management and usage.

Field-level encryption is supported at the driver layer and can be used to separately encrypt specified sensitive information such as accounts, passwords, prices, and mobile phone numbers. You can abandon full-database encryption and use field-level encryption to make business more flexible and secure.

Latest materialized views can cache computing results to make computing more efficient and logic less complex.

MongoDB 4.0 is the first NoSQL database that supports cross-document transactions. It combines the speed, flexibility, features, and ACID guarantee of document models.

Concurrent read and write operations enable new shard nodes to migrate data fast and bear service loads.

The transaction feature ensures that secondary nodes no longer block read requests due to log synchronization. The multi-node scaling feature is supported in all versions to significantly improve read capabilities.

All indexes are created when data is synchronized. Only the _id index is created in earlier versions. During data synchronization, the secondary node continuously reads new operation log information to ensure that the local database of the secondary node has enough space to store temporary data.

In earlier versions, mongos nodes are responsible for load balancing of sharded clusters. Multiple mongos nodes compete for a distributed lock. The node that obtains the lock performs load balancing tasks and migrates chunks between shard nodes. In MongoDB 3.4, the primary Configserver node is responsible for load balancing. This greatly improves the concurrency and efficiency of load balancing.

Many aggregation operators are added to MongoDB 3.4 to provide more powerful data analysis capabilities. For example, bucket can conveniently classify data. $grahpLookup supports more complex relational operations than $lookup in MongoDB 3.2. $addFields enables richer document operations such as summing some fields and saving them as a new field.

The zone concept is introduced for sharded clusters to replace the current tag-aware sharding mechanism. The zone feature can allocate data to one or more specified shard nodes. This feature allows you to conveniently deploy sharded clusters across data centers.

In earlier versions, strings stored in documents are always compared byte-by-byte regardless of Chinese, English, uppercase, or lowercase. After collation is introduced, the string content can be interpreted or compared based on the used locale. Case-insensitive comparison is also supported.

MongoDB 3.4 supports read-only views. MongoDB 3.4 virtualizes the data that meets a query condition into a special collection, on which you can perform further queries.