LAUNCHMongoDB 8.3 is built for the sub-100ms retrieval & zero downtime AI demands. Read blog >
AI DATAStop fighting your data layer. Get the memory & retrieval agents need to scale. Read blog >

MongoDB Early
Access Programs

Sign up to receive more information on the latest features that are shaping the future of MongoDB before they reach general availability (GA).

Sign Up
Sign up for more information
  • IT Executive (CIO, CTO, VP Engineering, etc.)
  • Business Executive (CEO, COO, CMO, etc.)
  • Architect
  • Business Development / Alliance Manager
  • DBA
  • Technical Operations
  • Director / Development Manager
  • Product / Project Manager
  • Software Developer / Engineer
  • Mobile Developer
  • Business Analyst
  • Data Scientist
  • Student
  • Other
(associated with your Atlas account)
  • MongoDB Extension for Hibernate ORM Framework
  • Collection and Database Level Atlas Restores
  • Atlas Stream Processing for Apache Iceberg Sink
  • Standby Clusters for Disaster Recovery In Atlas
  • Search and Vector Search with Enterprise Server
  • Horizontal Auto Scaling for Atlas Cluster
  • Automated Voyage AI Embeddings in MongoDB Vector Search for Atlas
  • MongoDB Extension for Hibernate ORM Framework
  • Collection and Database Level Atlas Restores
  • Atlas Stream Processing for Apache Iceberg Sink
  • Standby Clusters for Disaster Recovery In Atlas
  • Search and Vector Search with Enterprise Server
  • Horizontal Auto Scaling for Atlas Cluster
  • Automated Voyage AI Embeddings in MongoDB Vector Search for Atlas

Unlock the benefits of our early access programs

Experience MongoDB’s latest technologies and influence their direction.
realm_real_time_collaboration

Pre-release access

Exclusive access to upcoming features in beta before they become generally available.

general_features_support

Regular check-ins

White glove experience from the MongoDB Product and Engineering team and access to a dedicated community forum.

general_content_community

Collaborative innovation

Make a direct impact on the success of our products with a chance to co-develop.

community_edition_product_family

Global spotlight

A platform to share your story on our social channels and be part of events organized globally.


Current and upcoming features in preview

Illustration depicting the concept of data sharding.

Horizontal Auto Scaling

Horizontal auto-scaling is MongoDB’s fully managed horizontal scaling capability. It automatically adds shards when your cluster needs more capacity, redistributes sharded collection data in the background for balanced performance all without any manual intervention or application changes.

Request preview
An illustration of a hand holding a database server.
PUBLIC PREVIEW

MongoDB Model-Context-Protocol (MCP) Server

Connect MongoDB to AI tools with MCP Server for effortless, natural language data management.

Learn more
Vector Search illustration
PUBLIC PREVIEW

MongoDB Search and Vector Search with MongoDB Enterprise Server and Community Edition

Power search-driven experiences with MongoDB's native full-text and vector search. Use Community Edition for local development with features like autocomplete, fuzzy matching, and semantic vector search, or choose Enterprise Server for scalable, high-performance queries in Kubernetes.

Learn more
Illustration depicting MongoDB Vector Search
Public Preview

Automated Voyage AI Embeddings in MongoDB Vector Search for Atlas

Enable one-click AI powered semantic search on text data in MongoDB Atlas. Select a model in the vector index definition to automatically generate embeddings on data ingestion, updates and for queries using Atlas-managed Voyage AI models.

Request Preview
An illustration of a database

Collection and Database Level Atlas Restores

Restore specific collections or databases in MongoDB Atlas through the UI or API, minimizing downtime and keeping your cluster’s other collections unaffected.

Request preview
Illustration depicting clusters and a cloud database.

Standby Clusters for Disaster Recovery in Atlas

Ensure business continuity with MongoDB Atlas Standby Clusters by seamlessly recovering from outages with sub-minute recovery times and near-zero data loss, thanks to continuous cluster replication across regions or cloud providers.

Request Preview
Illustration of a terminal interface showing data stream processing.

Atlas Stream Processing for Apache Iceberg Sink

Write Change Stream data directly in the Iceberg format to S3 buckets. Simplify real-time data integration with external data warehouse ecosystems while maximizing performance and scalability.

Request preview
Automated Text Embedding in Vector Search illustration.
PUBLIC PREVIEW

Automated Embedding in Vector Search (in Community Edition)

Automated text embedding allows MongoDB Community users to create vector search indexes that automatically generate, store, and query text embeddings using Voyage AI models.

Learn more
Illustration showing cloud database clusters and servers.
Public Preview

Embedding and Reranking API on MongoDB Atlas

The Embedding and Reranking API is a new serverless API service that provides developers with direct access to Voyage AI’s frontier retrieval models natively within the MongoDB Atlas platform.

Learn more
An illustration of a magnifying glass next to a web page and data points to represent data insights.
Public Preview

Lexical Prefilters for MongoDB Vector Search

Lexical Prefilters enable advanced text and geo analysis filters in vector search, simplifying the creation of sophisticated applications that combine semantic understanding with precise text filtering.

Learn more
Illustration of education books
PUBLIC PREVIEW

MongoDB’s Multimodal Search Python Library

MongoDB’s Multimodal Search Python Library integrates MongoDB Vector Search, AWS S3, and Voyage AI’s voyage-multimodal-3, streamlining AI app development.

Learn more
An illustration of a relational database migration.
PUBLIC PREVIEW

Pre-Migration Analysis: Relational Migrator

Simplify migrations with automated pre-migration analysis in MongoDB Relational Migrator. Instantly assess migration feasibility and plan with confidence.

Learn more
Illustration representing flexible data access.
PUBLIC PREVIEW

MongoDB Extension for Hibernate ORM Framework

Integrate MongoDB with Java applications easily using JPA annotations, HQL, and native MongoDB queries (MQL). Enhance Hibernate projects with minimal changes, combining relational mapping with MongoDB’s flexible document capabilities for scalable, efficient data access.

Learn more
Illustration representing Queryable Data Encryption for text support and searchable queries.
PUBLIC PREVIEW

Queryable Encryption: Prefix, Suffix and Substring

Extend Queryable Encryption with support for text searches on encrypted data, enabling prefix, suffix, and substring queries alongside equality and range, all without server-side decryption.

Learn more
An illustration showing an automated computing process.
Public Preview

MongoDB for IntelliJ Plugin

Built for IntelliJ IDEA Ultimate, this plugin enables enterprise Java developers to write and test Java queries faster, receive proactive performance insights, and reduce runtime errors right in their IDE.

Learn more

Your path to early access

misc_send

Sign Up

Note: Participation may require a non-disclosure agreement (NDA).

general_features_automation

Get Accepted

If your use case fits, we’ll enroll you and send onboarding details.

general_events_breakout

Test and Share Feedback

Try out the feature and let us know what you think — your insights help shape the final product!

Atlas Stream Processing
“Our Acoustic Connect platform must be able to efficiently process and manage millions of marketing, behavioral, and customer signals as they occur. With Atlas Stream Processing, our engineers can leverage the skills they already have from working with data in Atlas to process new data continuously, ensuring our customers have access to real-time customer insights.”
John Riewerts
EVP, Engineering, Acoustic
View documentation
Atlas Stream Processing
“Our Acoustic Connect platform must be able to efficiently process and manage millions of marketing, behavioral, and customer signals as they occur. With Atlas Stream Processing, our engineers can leverage the skills they already have from working with data in Atlas to process new data continuously, ensuring our customers have access to real-time customer insights.”
John Riewerts
EVP, Engineering, Acoustic
View documentation
Vector Search
“We are using AI embeddings and Atlas Vector Search to go beyond full-text search with semantic meaning, giving context and memory to generative AI car-buying assistants. We are very excited that MongoDB has added Vector Search to Atlas, which greatly simplifies our engineering efforts.”
Nathan Clevenger
Founder & CTO, Drivly Inc
View documentation
Atlas Stream Processing
“Atlas Stream Processing enables us to process, validate, and transform data before sending it to our messaging architecture in AWS powering event-driven updates throughout our platform. The reliability and performance of Atlas Stream Processing have increased our productivity, improved developer experience, and reduced infrastructure costs.”
Cody Perry
Software Engineer, Meltwater
View documentation
Atlas SQL
“The Atlas SQL interface allows me to easily fit new, modern applications into existing IT landscapes for my customers. I’m better able to leverage MongoDB for companies that I’m leading through a digital transformation knowing they can seamlessly use their existing SQL-based tools for analytics.”
Michael Höller
Akazia Consulting
View documentation
MongoDB Time Series
“The migration to MongoDB time series from our existing time series database went easily. We saw a 3-5% performance improvement compared with our previous time series-based solution. The difference between our old solution and MongoDB's precision when calculating a count was eye-opening for us, where we do not have to face the count-distinct problem.”
István Kovács
CTO at Recart
View documentation
Local Experience with Atlas CLI
“Using the recently published local Atlas Docker image, we are now able to automate our tests for code that uses Atlas search. This makes development more robust, stable, and easier to distribute across our other environments. Using the Atlas CLI, we can simplify the index creation and even automate it.”
Kevin Fester
Software Engineer, Allthings
View documentation

Frequently Asked Questions

For further questions, please reach out to early-access@mongodb.com.