Announcing a Modernization Toolkit to Help Customers and Partners Modernize From Legacy DBs to MongoDB

Dana Groce and Prasad Pillalamarri
March 5, 2020 | Updated: November 11, 2020
#partners#migration#MongoDB Atlas

The best way way to migrate applications to the cloud is to modernize vs lift and shift. We’re excited to announce the general availability of a modernization toolkit with partners Informatica and Hitachi Vantara Pentaho which will allow customers to better move data from Oracle (RDBMS) to MongoDB while modernizing to the cloud.

Informatica

Informatica’s Enterprise Data Catalog (EDC) and Informatica Intelligent Cloud Services (IICS) will simplify the process of identifying and moving data into MongoDB utilizing a discovery-driven approach to data migration and integration. Users will be able to perform impact analysis, discover data relationships, and track lineage. Users will also be able to:

  • Design data migration/integration based on discovered assets
  • Apply transformations
  • Manage end to end life cycle of data management

Watch this short video to learn how Informatica helps accelerate data modernization from RDBMS to MongoDB

Pentaho

Pentaho simplifies and speeds the process of moving data from existing RDBMS databases into MongoDB, then enables further blending and analysis with new sources of data. Pentaho Data Integration’s no code, graphical designer includes:

  • Intuitive, drag-and-drop designer to orchestrate the data migration flow
  • Rich library of pre-built components to access, prepare and blend data from relational sources, big data stores on premises or in the cloud, enterprise applications and more
  • Ability to validate data in flight
  • Integrated enterprise scheduler for coordinating workflows and debugger for testing and tuning job execution

Watch the demo to see how Pentaho’s tools can help you move your legacy data from RDBMS to MongoDB

The combined tools support one-time movement of data from RDBMS into MongoDB at scale, as well as continuous data modernization, including change data capture, reconciliation, and validation procedures. We anticipate our system integrator partners, who help our customers with digital transformation and migrations to the cloud, will widely utilize these tools.

The MongoDB Modernization Scorecard

This tooling, along with MongoDB’s Modernization Scorecard, will help our customers evaluate the suitability of MongoDB for both new applications and application modernizations. The scorecard scores MongoDB and other databases against multiple criteria in each of the following categories of application requirements:

  • Data modeling
  • Query requirements
  • Performance & scalability
  • Availability & disaster recovery
  • Operational management
  • Deployment model & TCO

Customers today modernize to MongoDB by using bespoke frameworks and bulk data ingestion pipelines. This new solution provides a standard framework to move data to MongoDB and enables users to create modernization factories with substantial ROI, and at scale. This will also ensure 70:30 workloads are automated, increasing TCO savings and drastically reducing modernization project timelines.

Learn More About the Modernization Guide

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Hanabi Technologies Uses MongoDB to Power AI Assistant, Hana

For all the hype surrounding generative AI, cynics tend to view the few real-world implementations as little more than “fancy chatbots.” But for Abhinav Aggarwal, CEO of Hanabi Technologies, the idea of a generative AI-powered bot that is more than just an assistant was intriguing. “I’d been using ChatGPT since it launched,” said Aggarwal. “That got me thinking: How could we make a chatbot that was like a team member?” And with that concept, Hana was born. The problem with bots “Most generative AI chatbots do not act like people; they wait for a command and give a response,” said Aggarwal. “We wanted to create a human-like chatbot that would proactively help people based on what they wanted—automating reminders, for example, or fetching time zones from your calendar to correctly schedule meetings.” Hanabi’s flagship product, Hana, is an AI assistant designed to enhance team collaboration within Google Chat, working in concert with Google Workspace and its suite of products. “Our target customers are smaller companies of between 10 and 50 people. At this size you’re not going to build your own agent from scratch,” he said. Hana integrates with Google APIs to deliver a human-like assistant that chimes in with helpful interventions, such as automatically setting reminders and making sure meetings are booked in the right time zone for each participant. “Hana is designed to bring AI to smaller companies and help them collaborate in a space where they are already working—Google Workspace,” Aggarwal explained. The MongoDB Atlas solution For Hana to act like a member of the team, Hanabi needed to process massive amounts of data to support advanced features like retrieval-augmented generation (RAG) for better information retrieval across Google Docs and many other sources. And with a rapidly growing user base of over 600 organizations and 17,000+ installs, Hanabi also required a secure, scalable, and high-performing data storage solution. MongoDB Atlas provided a flexible document model, built-in vector database, and scalable cloud-based infrastructure, freeing Hanabi engineers to build new features for Hana rather than focusing on rote tasks like data extract, transform, and load processes or manual scaling and provisioning. Now, MongoDB Atlas handles a variety of responsibilities: Scalability and security: MongoDB Atlas’s auto-scaling and automatic backup features have enabled Hanabi to seamlessly grow its user base without the need for manual database management. RAG: MongoDB Atlas plays a critical role in Hana’s RAG functionality. The platform enables Hanabi to split Google Docs into small sections, create embeddings, and store these sections in Atlas’s vector database. Development Processes: According to Aggarwal, MongoDB’s flexibility in managing changing schemas has been essential to the company’s fast-paced development cycle. Data Visualization: Using MongoDB Atlas Charts has enabled Hanabi to create comprehensive dashboards for real-time data visualization. This has helped the team track usage, set reminders, and optimize performance without needing to build a manual dashboard. Impact and results With MongoDB Atlas, Hanabi can successfully scale Hana to meet the demands of its rapidly expanding user base. The integration is also enabling Hana to offer powerful features like automatic interactions with customers, advanced information retrieval from Google Docs, and manually added memory snippets, making it an essential tool for teams around the world. Next steps Hanabi plans to continue integrating more tools into Hana while expanding its reach to personal Gmail users. The company is also rolling out a new automatic-interaction feature, further enhancing Hana’s ability to proactively assist users without direct commands. MongoDB Atlas remains a key component of Hanabi’s stack, alongside Google Kubernetes Engine, NestJS, and LangChain, enabling Hanabi to focus on innovating to improve the customer experience. Tech Stack MongoDB Atlas Google Kubernetes Engine NestJS LangChain Are you building AI apps? Join the MongoDB AI Innovators Program today! Successful participants gain access to free MongoDB Atlas credits, technical enablement, and invaluable connections within the broader AI ecosystem. If your company is interested in being featured, we’d love to hear from you. Connect with us at ai_adopters@mongodb.com.

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