CedarDB wants one database to handle both transactions and analytics, as AI agents raise the stakes

Databases have traditionally been built for one of two jobs. Analytical databases help businesses spot trends and answer questions, while operational databases store the day-to-day records of transactions, like orders and payments. But the Munich-based database engine CedarDB supports both, and its approach has gained relevance with the rise of agentic AI, its co-founder and CEO Moritz Sichert told TechCrunch.

传统上，数据库的构建通常只服务于两种任务之一。分析型数据库帮助企业发现趋势并回答问题，而操作型数据库则存储日常交易记录，例如订单和付款。但据其联合创始人兼首席执行官 Moritz Sichert 向 TechCrunch 透露，总部位于慕尼黑的数据库引擎 CedarDB 两者兼顾，且随着代理式人工智能（agentic AI）的兴起，其方法已变得愈发重要。

CedarDB has been in the making for the last decade, but its current momentum stems from enterprise companies whose existing data stacks may have been well suited to storing years of transactions, yet less suited to quickly answering analytical questions asked in natural language about that data. CedarDB’s questioning of the divide between analytical and operational queries is a by-product of its focus on efficiency.

CedarDB 的研发历时十年，但其目前的增长势头源于那些企业客户——他们现有的数据栈或许很适合存储多年的交易记录，却难以快速回答关于这些数据的自然语言分析问题。CedarDB 对分析型查询与操作型查询之间界限的质疑，正是其专注于效率的副产品。

The company is a Technical University of Munich spinout based on Umbra, a research project that was built from scratch to beat legacy database engines at processing speed by making the most of modern hardware. With five Umbra researchers as its co-founders, CedarDB kept that approach, promising faster performance without requiring more CPUs or processing power and memory — and requiring few changes from customers.

该公司是从慕尼黑工业大学剥离出来的项目，基于 Umbra 开发。Umbra 是一个从零开始构建的研究项目，旨在通过充分利用现代硬件，在处理速度上超越传统的数据库引擎。CedarDB 由五名 Umbra 研究人员共同创立，并延续了这一方针，承诺在无需增加 CPU、处理能力或内存的情况下提供更快的性能，且客户几乎无需进行任何更改。

In particular, its team made sure CedarDB was compatible with PostgreSQL, an open source database system. According to Sichert, this compatibility with the popular database helps keep switching costs low, since users don’t need to rebuild their apps. It also has an added advantage: CedarDB follows the logic LLMs are most familiar with as a result of their training.

特别值得一提的是，其团队确保了 CedarDB 与开源数据库系统 PostgreSQL 的兼容性。Sichert 表示，与这种流行数据库的兼容有助于降低转换成本，因为用户无需重建应用程序。此外，它还有一个额外优势：CedarDB 遵循大语言模型（LLM）在训练过程中最熟悉的逻辑。

That decision is one of many choices that proved lucky in retrospect, Sichert said. But it wasn’t all luck. In a blog post, co-founder Christian Winter detailed key priorities the team set after leaving academia, “such as reliability, fault tolerance and compatibility with popular tools.” Not all of the answers were obvious. The team strongly debated whether it should launch a cloud offering right away.

Sichert 说，回顾过去，这一决定是众多幸运选择之一。但这并非全靠运气。联合创始人 Christian Winter 在一篇博客文章中详细介绍了团队离开学术界后设定的关键优先事项，“例如可靠性、容错能力以及与流行工具的兼容性。”并非所有答案都显而易见。团队曾就是否应立即推出云服务进行了激烈的辩论。

In the end, it launched CedarDB Enterprise as an on-premise offering alongside its free version, CedarDB Community Edition, both announced in May of last year at the same time as it announced a €5.3 million seed funding round (approximately $6 million). The cloud offering was only delayed, though, not abandoned.

最终，他们推出了 CedarDB Enterprise 作为本地部署版本，并同时发布了免费版本 CedarDB Community Edition。两者均于去年 5 月宣布，与 530 万欧元（约合 600 万美元）的种子轮融资同时公布。不过，云服务只是被推迟了，并未被放弃。

After conducting beta testing with users who had signed up for its waitlist, the company on Wednesday announced limited availability of CedarDB Cloud onstage at TechCrunch Disrupt, where it’s competing with 20 other startups vying to win TechCrunch’s prestigious Startup Battlefield competition. A fully managed, cloud-hosted version will likely help CedarDB expand its user base beyond large enterprises.

在对候补名单上的用户进行内测后，该公司周三在 TechCrunch Disrupt 大会上宣布 CedarDB Cloud 有限度开放。目前，该公司正与另外 20 家初创公司同台竞技，角逐 TechCrunch 著名的“创业战场”（Startup Battlefield）竞赛。一个完全托管的云端版本很可能会帮助 CedarDB 将用户群扩展到大型企业之外。

It will also make it better prepared to compete with the likes of Databricks, a major data company that seems to have reached the same conclusion as the German startup. 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.”

这也将使其更有能力与 Databricks 等大型数据公司竞争，后者似乎也得出了与这家德国初创公司相同的结论。在 6 月份的 Data + AI 峰会上，这家美国公司将“代理时代”作为其推出 LTAP 的理由。LTAP 是一种新的数据架构，旨在“在湖中的单一存储副本上统一交易、分析、流处理和操作数据”。

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.”

现在判断这会带来多大的颠覆性还为时过早，但 Sichert 将 Databricks 的举动解读为 CedarDB 所做之事存在市场需求的又一信号。这家初创公司计划利用目前 14 人的团队服务首批云用户，但 Sichert 预计，一旦获得更多牵引力，就需要扩大团队规模。“而这正是我们将进行下一轮融资的时候。”