MongoDB makes multiple announcements, including Relational Migrator GA

Friday, 23 June 2023 01:01

MongoDB makes multiple announcements, including Relational Migrator GA

MongoDB CTO Mark Porter

Database vendor MongoDB's Australian-developed MongoDB Relational Migrator is now generally available. The company made several other announcements at its developer conference, so please keep reading.

MongoDB Relational Migrator simplifies the task of application modernisation by automating migrations from legacy databases such as Oracle Database, Microsoft SQL Server, MySQL and PostgreSQL to MongoDB Atlas.

According to the company, all that's needed is to point MongoDB Relational Migrator to an old database, and then it automatically generates the required data schema and code, and then migrates the data to MongoDB Atlas with no downtime required.

Customers can then run the modernised application in a test environment before putting it into production.

Relational Migrator includes the ability to continuously sync the old and new databases.

“Customers often tell us it’s crucial that they modernise their legacy applications so they can quickly build new end-user experiences that take advantage of game-changing technologies and ship new features at high velocity. But they also say that it’s too risky, expensive, and time consuming, or that they just don’t know how to get started,” said MongoDB chief product officer Sahir Azam.

“With MongoDB Relational Migrator, customers can now realise the full potential of software, data, and new technologies like generative AI by migrating and modernising their legacy applications with a seamless, zero-downtime migration experience and without the heavy lifting. It’s now easier than ever to modernise applications and create innovative end-user experiences at the speed and scale that modern applications require with MongoDB Atlas.”

Perth-based Powerledger was among the early users of Relational Migrator.

CTO Dr Vivek Bhandar said "We needed to demonstrate our platform’s ability to ingest a much higher volume of data and cater to the one billion users we aim to serve in the future, which required a level of scalability and flexibility that our previous relational database couldn’t offer.

“Migrating an entire database is a pretty bold and risky endeavour. Our main priorities – and challenges – were to do a complete data platform migration, as well as add in scalability and flexibility without disrupting the platform or hindering data security. Amazingly, using MongoDB Relational Migrator, we didn’t experience any disruption or downtime.”

MongoDB CTO Mark Porter said “We are incredibly proud of our talented Australian engineering team which have made Relational Migrator a reality. Australia is a core innovation hub for MongoDB, with our local engineering team playing a huge role in delivering the long term product vision for the company, which then ends up in the hands of thousands of organisations all around the world.”

“Relational Migrator is a perfect example of engineering-led innovation, and I am excited to see it being rolled out globally after being successfully trialled by local Australian customers such as renewable energy provider Powerledger. More than a simple feature, Relational Migrator is a game changer: it will help so many organisations previously stuck with traditional SQL databases to move to a modern data platform,” he added.

“I am looking forward to seeing more great innovations come out of our local Australian engineering team, especially around artificial intelligence (AI), data visualisation, analytics and our all important storage engine, the team are working on many exciting projects in these fields.”

In related news, MongoDB made four announcements aimed at making it easier and quicker to build modern applications.

Organisations using MongoDB on AWS can now use C#, Go, Java and Python (in addition to existing support for Javascript and Typescript) in conjunction with the AWS Cloud Development Kit to create, manage and update MongoDB Atlas resources via infrastructure as code mongodb.com/atlas/aws-cloudformation. .

The Kotlin Driver for MongoDB provides official support for building server-side applications on MongoDB using Kotlin.

The MongoDB Atlas Kubernetes Operator simplifies the use of Atlas within Kubernetes environments.

The open-source (but MongoDB-maintained) PyMongoArrow library helps with analytics by allowing developers to efficiently convert data stored on MongoDB using popular frameworks such as Apache Arrow Tables, Pandas DataFrames, or Numpy Arrays.

“Our long-term vision is to create a developer data platform that removes as much builder friction as possible and makes it easier for developers to do what they do best – build,” said MongoDB senior vice president of product Andrew Davidson.

“Developers choose MongoDB Atlas because it’s the best place to quickly build applications that can make the most out of their data. We continually hear from developers that they want to be able to use even more tools seamlessly on MongoDB Atlas, so with these additional integrations and expanded features, we are taking another step in fulfilling our mission to meet developers where they are and to provide the best possible building experience with the least amount of friction.”

Given that AI is one of 2023's hottest topics. it's not surprising that MongoDB made several announcement relevant to that space.

MongoDB Atlas Vector Search allows large language models to access data stored in Atlas databases. It is integrated with the open source LangChain and LlamaIndex frameworks, helping to access LLMs from MongoDB partners (including, AWS, Databricks, Google Cloud, Microsoft Azure, and MindsDB) and model providers (including Anthropic, Hugging Face, and OpenAI) to generate vector embeddings and build AI-powered applications on MongoDB Atlas.

MongoDB Atlas Search Nodes provide dedicated infrastructure for customers to scale search workloads independent of their database, enabling workload isolation, resource optimisation, and better performance at scale. This allows the use of dedicated infrastructure to seamlessly scale MongoDB Atlas Vector Search and MongoDB Atlas Search workloads with greater flexibility.

MongoDB Atlas Stream Processing provides a single interface to easily extract insights from high-velocity and high-volume streaming data (such as that from IoT devices or browsing behaviour). It helps the development of applications that can analyse data in real time to adjust behaviour and inform business operations (such as highly personalised promotional offers or fraud detection and prevention).

MongoDB Time Series collections provide scaling enhancements and the ability to modify time series data, giving customers more control over their data at scale. This can result in better storage efficiency, improved query speeds, and improved data governance.

MongoDB Atlas Online Archive and Atlas Data Federation now support Microsoft Azure in addition to AWS, providing more opportunities to automatically tier Atlas databases to the most cost-effective cloud object storage option while retaining the ability to query.

“The new MongoDB Atlas capabilities announced today are an answer to the feedback we get from customers every day – they love that their teams are able to quickly build and innovate with MongoDB Atlas and want to be able to do even more with it across the enterprise,” said MongoDB president and CEO Dev Ittycheria.

“With the new features we’re launching today, we’re further supporting customers running the largest, most demanding, mission-critical workloads that require continually increasing scalability and flexibility, so they can unleash the power of software and data with next-generation applications that will drive the future of their businesses using a single developer data platform with MongoDB Atlas.”

The MongoDB AI Innovators Program provides organisations building AI technology access to credits for MongoDB Atlas, partnership opportunities in the MongoDB partner ecosystem, and go-to-market activities with MongoDB to accelerate innovation and time to market.

These credits are also available via AWS, Google Cloud and Microsoft Azure.

Separately, a new initiative in conjunction with Google Cloud aims to promote the development of new classes of applications using generative AI.

Google Cloud's Vertex AI foundational models can be used seamlessly with MongoDB Atlas Vector Search, the MongoDB and Google Cloud professional services teams can help with rapid prototyping of such applications, and subsequently optimise the nearly-finished applications for production use.

“With the shift in technology powered by generative AI taking place today, the future of software and data is now, and we’re making it more evenly distributed for developers with MongoDB Atlas,” said MongoDB executive vice president of worldwide partnerships Alan Chhabra.

“This shift begins with developers, and we want to democratise access to game-changing technology so all developers can build the next big thing. With MongoDB Atlas and our strategic partnership with Google Cloud, it’s now easier for organisations of all shapes and sizes to incorporate AI into their applications and embrace the future.”

Google Cloud corporate vice president of global ecosystem and channels Kevin Ichhpurani said “Generative AI represents a significant opportunity for developers to create new applications and experiences and to add real business value for customers.

“This new initiative from Google Cloud and MongoDB will bring more capabilities, support, and resources to developers building the next generation of generative AI applications.”

Finally, there is MongoDB Atlas for Industries, an accelerator program for specific industries, starting with financial services, to be followed this year by manufacturing and automotive, insurance, healthcare, retail and other currently unspecified industries.

MongoDB has achieved the AWS Financial Services Competency, and MongoDB is part of the Temenos Banking Cloud.

The program includes innovation workshops, access to industry-specific partner integrations and toolchains, 'jumpstart' assessments by MongoDB professional services and industry experts, and tailored MongoDB University courses and learning materials.

Bendigo and Adelaide Bank cloud platforms service owner Matt Vermeer said "The expertise that MongoDB delivered from working with other large customers in financial services combined with the MongoDB Atlas developer data platform, was vital in helping us transform our organisation for the future.

“We believe our partnership with MongoDB will help us accelerate this continued transformation of our business, deliver our technology strategy, and ultimately grow our organisation to achieve our vision of becoming Australia’s bank of choice by feeding into the prosperity of customers and their communities.”

MongoDB ANZ country manager Anoop Dhankhar said "At MongoDB we work with many financial services institutions across Australia, covering large banks to fintech start-ups, and what we are seeing across the board is the need for technology solutions and data strategies that meet specific industry needs. This is why I am excited about the launch of Atlas for Financial Services as it supports our local FSI customers in building multi-cloud and data strategies that solve for resilience, availability and compliance, and accompany them in their very unique data-driven journeys.

"The financial services sector is increasingly data-dependent, which creates a lot of complexity and raises concerns: on one hand financial services institutions want to reap the benefits of data to drive growth and respond to customer needs, but on the other they need to respond to growing data security and compliance challenges.

"Just recently, the Australian financial services industry shared its concerns about the challenges surrounding increased regulatory requirements, which led to the APRA delaying the implementation of the new CPS 230 framework. This is a great example of the complex regulatory challenges Australian FSI organisations are faced with and the extra support and guidance they need to rethink their cloud and data strategies so they are fit for purpose."

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