ClickHouse
Powering agentic systems with millisecond queries at petabyte scale.
Powering agentic systems with millisecond queries at petabyte scale. Langfuse is now part of ClickHouse. Discover the leading open-source platform for LLM observability, evaluations, and prompt management. Ideal for building, monitoring, and optimizing AI applications at scale. Deliver instant insights and dashboards at scale. Analyze billions of rows in real time with millisecond results. Store and query logs, metrics and traces at scale using ClickStack, the open source observability stack powered by ClickHouse. Analyze and explore data instantly for insights and apps. Scale faster by offloading heavy workloads. Power machine learning and GenAI with blazing-fast vector search, instant aggregations, and scalable training. “ClickHouse played an instrumental role in helping us develop and ship Claude 4.” “ClickHouse checked every box. We have availability, we have speed, we have durability. We have everything we could want.” “We needed something to slice and dice real-time data, like rides and driver hours across cities and regions where Lyft runs. Using ClickHouse resulted into a lot of performance benefits for us with huge cost savings for the org.” ClickHouse is faster than most traditional data warehouses and databases and is most often used when real-time queries on large datasets are necessary at an affordable cost. However, developers also often use ClickHouse on top of their CDWH or OLTP databases to act as a “speed layer” within their existing infrastructure. OLAP stands for “online analytical processing” which contrasts from OLTP, or “online transaction processing.” As the name suggests, OLAP databases perform significantly better compared to OLTP databases for analytical workloads common with large datasets. In order to easily process large amounts of data, ClickHouse uses highly optimized compression techniques and vectorized query execution to maximize CPU efficiency.
MongoDB Atlas Vector
Based on the social mentions, MongoDB Atlas Vector appears to be gaining positive traction in the AI/ML community, with users appreciating its unified approach to document and vector storage that eliminates the need for multiple tools. The platform is being praised for its integration capabilities, particularly with VoyageAI embeddings, and its ability to scale reliably for production applications (as evidenced by Heidi's 81 million medical consultations). Users seem to value the comprehensive tooling ecosystem, including VS Code extensions, educational resources like skill badges, and optimization features like vector quantization for improved performance and cost efficiency. Overall sentiment suggests MongoDB Atlas Vector is viewed as a developer-friendly, enterprise-ready solution that simplifies AI application development by providing a single platform for both traditional and vector data needs.
ClickHouse
MongoDB Atlas Vector
ClickHouse
MongoDB Atlas Vector
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ClickHouse
MongoDB Atlas Vector
