March 26, 2024: Today, Canonical announced the release of Charmed MongoDB, an enterprise solution for MongoDB® that comes with advanced automation features, multi-cloud capabilities and comprehensive support. 

MongoDB® is one of the most widely used databases worldwide. It provides powerful  capabilities for scaling, consistency and fault tolerance , making it a popular choice for organisations of all sizes and in various industries. Charmed MongoDB is an enterprise drop-in replacement for the MongoDB® Community version with the advanced features organisations need in their production environment.

“As part of our open source data solution portfolio, Charmed MongoDB is designed to meet the demands of modern deployments”, said Cedric Gegout, VP of Product at Canonical. “Organisations can deploy Charmed MongoDB with confidence, knowing they are backed by Canonical’s commitment to performance in any cloud environment, alongside 10 years of support  and security maintenance.”

Hyper-automated MongoDB^®, available on any cloud

The Charmed MongoDB operator deploys and runs MongoDB® on physical, virtual machines (VM) and other cloud and cloud-like environments, including AWS, Azure, OpenStack and VMWare.

The solution comes with automation features that simplify the deployment, scaling, design, and management of MongoDB®, ensuring reliability. In addition to these capabilities, Charmed MongoDB offers enterprise-level features such as high availability, sharding, audit logging, backup and restore, user management, and Transport Layer Security (TLS). 

Secured and supported for 10 years

For organisations looking for fast security patching against Common Vulnerabilities and Exposures (CVEs), Charmed MongoDB offers comprehensive security maintenance. Canonical’s Charmed MongoDB offers a cost-effective, subscription model that includes 10 years of security maintenance and 24/7 support, providing the stability and peace of mind necessary for organisations to run MongoDB® in production. 

Simple pricing per node

Charmed MongoDB is part of Canonical’s data solutions portfolio. Customers purchase 24/7 or weekday enterprise support on a per-node basis through the Ubuntu Pro + Support plan, which covers  all applications within the portfolio, including Charmed Kafka and Charmed Spark as well as solutions for AI offered by Canonical such as Charmed Kubeflow and Charmed MLFlow.

This convenient subscription per node and lack of software licence fees makes Canonical’s offering compelling for organisations looking to run database solutions like MongoDB® with more control over their TCO. Budgeting and financial planning are straightforward and predictable.

Get started with Charmed MongoDB

To get started with Charmed MongoDB, users can refer to the documentation available at Charmhub. For more information about Charmed MongoDB, visit canonical.com/data/mongodb.

Canonical is also delighted to offer Charmed MongoDB training in collaboration with Cloudbase Solutions. This program is designed to help individuals get started with Charmed MongoDB through in-person or virtual training.

Additional resources

Webinar: MongoDB® for Modern Data Management

Whitepaper: MongoDB® Security and Support

Whitepaper: MongoDB® for enterprise data management

Learn more about Charmed MongoDB Managed Service

Learn more about Data Solutions Advisory at Canonical

Trademark Notice

“MongoDB” is a trademark or registered trademark of MongoDB Inc. Other trademarks are property of their respective owners. Charmed MongoDB is not sponsored, endorsed, or affiliated with MongoDB, Inc.

Canonical is delighted to be a technology partner at the Data Innovation Summit (DIS) in 2024. We are proud to showcase our Data and AI solutions through our conference talk and technology in practice sessions. The event will take place in Kistamässan, Stockholm on April 24-25, 2024. Visit us at booth C71 to learn how open source data and AI solutions can help you take your models to production, from edge to cloud.

Data and AI: get first-hand insights from Canonical experts

The modern enterprise can use AI algorithms and models to learn from their treasure troves of big data, and make predictions or decisions based on the data without being explicitly programmed to do so. What’s more, the AI models grow more accurate over time. 

The magic is in the melding of AI and big data. Data of incredible volume, velocity, and variety is fed into the AI engine, making the AI smarter. Over time, less human intervention is needed for the AI to run properly; in time, the AI can deliver deeper insights—and strategic value—from the ever-increasing pools of data, often in real time. 

In today’s competitive business environment, your AI and data strategies need to be more interconnected than ever. According to an MIT Technology Review survey, 78% of CIOs say that scaling AI to create business value is the top priority of their enterprise data strategy, and 96% of AI leaders agree. Nearly three out of four CIOs also say that data challenges are the biggest factor jeopardising AI success.

The Data Innovation Summit is a significant event in the field of Data and AI, especially in the Nordics. It brings together professionals, enterprise practitioners, technology providers, start-up innovators, and academics working with data and AI. We at Canonical are delighted to announce that we will be participating in this event and sharing our expertise in Data and AI.

Canonical is a well-known publisher of Ubuntu, which is the preferred operating system (OS) for data scientists. In addition to the OS, Canonical offers an integrated data and AI stack. We provide the most cost-effective options to help you gain control over your Total Cost of Ownership (TCO), and ensure reliable security maintenance, allowing you to innovate at a faster pace.

Canonical DIS talk: open source DataOps and MLOps

Canonical data and AI Product Managers, and Andreea Munteanu and Michelle Anne Tabirao will be speaking about open source for your DataOps and MLOps.

Talk description

Open source data and AI tools enable organisations to create a comprehensive solution that covers all stages of the data and machine learning lifecycle. This includes correlating data from various sources, regardless of their collection engine, and serving the model in production. Together, DataOps and MLOps drive the collaboration, communication, and integration that great data and AI teams need, making them essential to the model lifecycle. DataOps is an approach to data management that focuses on collaboration, communication, and integration among data engineers, data scientists, and other data-related roles to improve the efficiency and effectiveness of data processes. MLOps is a set of practices that combines machine learning, software development, and operations to enable the deployment, monitoring, and maintenance of machine learning models in production environments.

In this talk, we will explore how to build an end-to-end solution for DataOps and MLOps using open-source solutions like databases, ML and analytics tools such as OpenSearch, Kubeflow, and MLFlow. Professionals can focus on building ML models without spending time on the tooling operational work. We will highlight some use cases, e.g. in the telco sector, where they use MLOps and DataOPs to optimise the telco network infrastructure and reduce power consumption.

Attendees will learn about the critical factors to consider when selecting tools and best practices needed for building a robust, production-grade ML project.

Come and meet us at DIS 2024

If you are interested in building or scaling your data and AI projects with open source solutions, we are here to help you. Visit our Data and AI offerings to explore our solutions.

Learn more about our Data and AI solutions

• Ubuntu AI podcast: dive into data and AI on the go
• Big data and AI WP: build a smarter enterprise with a secure, integrated open source stack
• MongoDB for enterprise data management WP: MongoDB benefits for modern enterprise data management, use cases for financial, telecommunications and automotive industries
• MLOps toolkit: from hardware to applications, discover the key factors to consider when building your machine learning toolkit
• Using PostgreSQL to power your AI applications: learn what PostgreSQL has to offer for your AI projects
• Canonical Data: enterprise data solutions for rapid innovation at any scale
• Canonical AI: take your models to production with open source AI