Source URL: https://blog.redplanetlabs.com/2025/03/04/how-multiply-went-from-datomic-to-xtdb-to-rama/
Source: Hacker News
Title: Multiply Went from Datomic to XTDB to Rama
Feedly Summary: Comments
AI Summary and Description: Yes
Summary: The text outlines how Multiply, an AI-powered collaboration platform, transitioned from using traditional databases to employing the innovative Rama platform to enhance their backend architecture. This shift allowed them to overcome limitations associated with conventional database models, thereby increasing performance, scalability, and development efficiency.
Detailed Description:
Multiply, a collaborative platform utilizing AI, reimagined its entire backend infrastructure to solve critical challenges faced with previous database implementations. The organization initially used Datomic and then XTDB but decided to adopt Rama, which was announced as a solution to their database-related issues. The analysis highlights several significant insights:
– **Challenges with Traditional Databases:**
– Limited Data Models: Traditional databases such as Postgres, MongoDB, and Redis typically support a limited number of indexing strategies and data models, leading to rigidity in application design.
– Understandability Issues: The fixed data models of conventional databases obscured the holistic understanding of the system, making it challenging to manage and integrate different components.
– Performance Limitations: Running deep live queries posed significant bottlenecks, making fault tolerance across nodes difficult.
– **Advantages of the Rama Platform:**
– **Flexibility:** Rama’s unique indexing model accommodates infinite data structures, allowing Multiply to tailor their infrastructure to their application’s needs without forcing adaptations.
– **Improved Development Workflow:** With Rama, Multiply streamlined its backend processes by reducing the amount of custom infrastructure needed previously. This led to accelerated feature development and simplifications in code management.
– **Synchronous & Asynchronous Management:** The unified handling of synchronous and asynchronous operations under Rama eliminated the complexity of using multiple systems for data storage and computation.
– **Implementing PStates:**
– Rama’s data structures, called PStates, empower Multiply to define numerous indexing and schema configurations tailored to their specific use cases.
– Each PState supports various use cases, such as tracking login information or storing LLM responses, enabling rapid queries and low-latency performance.
– **Simplified Deployment and Management:**
– Deploying on five nodes with built-in replication features reduced the complexity typically associated with setting up databases in production.
– The built-in monitoring and backup features provided by Rama enhanced operational reliability and maintenance ease.
– **Strategic Benefits:**
– The transition to Rama has fundamentally altered Multiply’s operational dynamics, allowing their small team to work efficiently, focus on core business logic, and harness AI capabilities without being bogged down by conventional database constraints.
Multiply’s experience with Rama exemplifies how leveraging innovative data management platforms can revolutionize operational efficiency in AI-powered applications while also simplifying compliance and data governance challenges typically associated with traditional databases. This transition reflects a significant shift towards more adaptive and scalable infrastructure solutions, crucial for modern tech-driven enterprises.