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CedarDB Combines Transactional and Analytical Workloads for Agentic AI

CedarDB, a Munich-based database engine, supports both transactional and analytical workloads, gaining relevance with the rise of agentic AI, according to its cofounder and CEO Moritz Sichert.

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CedarDB's Dual-Functionality Approach and Agentic AI Relevance

CedarDB, a Munich-based database engine, supports both transactional and analytical workloads, a feature that has gained relevance with the rise of agentic AI, according to its cofounder and CEO Moritz Sichert, as reported by TechCrunch. The company has been in development for the last decade, but its current momentum is driven by enterprise companies that find their existing data stacks well-suited for storing years of transactions but less capable of quickly answering analytical questions posed in natural language. CedarDB also has an added advantage: it follows the logic LLMs are most familiar with as a result of their training.

CedarDB's Technical Foundations and Compatibility

CedarDB is built on a foundation that emphasizes performance and compatibility, leveraging the expertise of its cofounders, many of whom are former Umbra researchers. The database is designed to handle both transactions and analytics, aiming to reduce the need for additional hardware resources such as CPUs, memory, or processing power. This approach is intended to provide faster performance with minimal changes required from customers.

A key aspect of CedarDB's design is its compatibility with PostgreSQL, an open-source database system. According to Sichert, this compatibility helps lower switching costs for users, as they do not need to rebuild their applications from scratch. This compatibility is a strategic move to ensure a smoother transition for organizations already using PostgreSQL, making CedarDB an attractive option for those looking to consolidate their database infrastructure.

CedarDB's Product Launches and Market Expansion

CedarDB has launched its Enterprise version as an on-premise solution, alongside its free CedarDB Community Edition, both announced in May of last year. The company also secured €5.3 million in seed funding (approximately $6 million) at the same time. Following beta testing with waitlisted users, CedarDB announced limited availability of CedarDB Cloud at TechCrunch Disrupt, where it is competing with 20 other startups for TC’s Startup Battlefield competition. A fully managed, cloud-hosted version is expected to help CedarDB expand its user base beyond large enterprises.

Industry Context and Competitor Insights

At its Data + AI Summit in June, the American company cited “the agentic era” as the reason why it was launching LTAP, a new data architecture aiming to “[unify] transactions, analytics, streaming, and operational data on a single copy of storage in the lake.” It is too early to tell how disruptive this might be, but Sichert interprets Databricks’ move as another sign that there is demand for what CedarDB does. The startup plans to serve its first cloud users with its current team of 14 people; but Sichert expects it will need a larger team once it gets more traction. “And this is where we would raise our next round.”