Analysis of the Impact of ClickHouse's $15 Billion Valuation on Database Industry Investments

Based on collected data and market information, I will provide you with a

.

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ClickHouse completed a

on January 16, 2026, led by Dragoneer Investment Group, with participation from Bessemer Venture Partners, GIC, Index Ventures, Khosla Ventures, Lightspeed Venture Partners, T. Rowe Price Associates, and WCM Investment Management[1][2]. This financing brought the company’s valuation to , representing a from its $6.35 billion valuation in May 2024, with its valuation growing 2.5-fold in less than a year[1][2].

This valuation surge reflects several key factors:

• Driven by AI Workloads
  : As enterprises deploy AI applications on a large scale, demand for real-time data analytics and low-latency queries has surged
• 250% ARR Growth
  : ClickHouse Cloud’s annual recurring revenue (ARR) has grown by 250%, demonstrating strong commercialization capabilities
• 3,000+ Customer Base
  : Including leading enterprises such as Meta, Tesla, Sony, Capital One, and Polymarket[1]

ClickHouse has recently completed two important strategic initiatives:

• Acquisition of Langfuse
  : Enhances LLM (Large Language Model) observability capabilities and enters the AI monitoring track
• Launch of Native PostgreSQL Service
  : Unifies transactional and analytical workloads to expand market space

Unlike traditional data warehouses such as Snowflake and Databricks, ClickHouse focuses on

rather than internal reporting analysis. This differentiated positioning has given it unique advantages in the AI era[1].

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According to industry data, the global financing amount in the database and data infrastructure sector has grown from $12 billion in 2023 to an estimated $25 billion in 2025, with a

[3][4]. This trend is mainly driven by the following factors:

Driving Factor	Specific Performance
AI Application Boom	Large-scale model training and inference require massive real-time data processing capabilities
Multi-Cloud Deployment Demand	Enterprises avoid vendor lock-in and prefer open ecosystems
Real-Time Analytics Demand	Shift from batch processing to real-time stream processing
Cost Optimization Pressure	Refined cloud cost management has become a necessity

Valuations of leading enterprises in the database and data infrastructure sector have shown significant growth:

• Databricks
  : Completed a $4 billion Series L financing in December 2025, valuing the company at
  $134 billion
  , representing a 123% increase from its $60 billion valuation at the end of 2024[3]
• Snowflake
  : Currently has a market capitalization of
  $72 billion
  , with an analyst consensus target price of $282.50, representing a 34% upside from the current price[5]
• Datadog
  : Currently has a market capitalization of
  $41.7 billion
  . Despite a 14% decline in its stock price over the past year, it still received a “Buy” rating from 82% of analysts[6]

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Company	Type	Valuation/Market Capitalization	Key Financial Indicators	Valuation Logic
ClickHouse	Private	$15 billion	250% ARR growth	High growth, AI-driven, subscription model
Snowflake	Public	$72 billion	P/S: 8.5x, Revenue $2.1 billion (TTM)	Cloud data warehouse leader, multi-cloud ecosystem
Datadog	Public	$41.7 billion	P/E: 388x, Revenue $3.5 billion (TTM)	Observability leader, margin improvement
Databricks	Private	$134 billion	ARR approximately $3 billion	Unified data lakehouse, AI-native platform
MongoDB	Public	$32.5 billion	Revenue $1.4 billion (TTM)	NoSQL leader, Atlas cloud growth

ClickHouse’s $15 billion valuation corresponds to approximately 25x P/S (based on revenue estimates), significantly higher than Snowflake’s 8.5x and Datadog’s 14.2x. This valuation divergence may trigger

of the following companies:

• Snowflake
  : As a cloud data warehouse leader, its valuation has room for expansion if it can prove that AI features (such as Cortex, vector search) can accelerate consumption growth. Currently, 77.6% of analysts have given it a “Buy” rating[5]
• Datadog
  : Occupies a leading position in the observability and AI operations and maintenance fields. Its high 388x P/E reflects the market’s premium expectations for its growth prospects[6]
• MongoDB
  : With its Atlas cloud service and vector search capabilities, MongoDB’s potential in AI application scenarios is being re-recognized, with its stock price rising 42% over the past year[7]

The large-scale financings of ClickHouse and Databricks indicate that

. This sentiment may spill over to:

• Increase investors’ risk appetite for the entire SaaS/data software sector
• Attract more capital inflows into AI-related data processing enterprises
• Create a favorable environment for potential IPOs (although the IPO window has not fully recovered)

Valuation divergence reflects the market’s pricing differences for different business models:

Valuation Premium Factors	Discount Risk Factors
AI-native capabilities	Uncertain profitability
Real-time processing capabilities	Customer concentration
High growth (>100% ARR)	Intensified competition (cloud vendors entering the market)
Open ecosystem	Macroeconomic uncertainty

It is worth noting that despite the hot financing of ClickHouse,

:

• Snowflake
  : Fell 12.61% in the past 3 months, mainly affected by market concerns about the speed of AI monetization[5]
• Datadog
  : Fell 22.14% in the past 3 months, reflecting valuation digestion and growth expectation adjustments[6]

This indicates that the high valuations in the private market require

to be transmitted to the secondary market, and there is a certain divergence in valuations between the primary and secondary markets at present.

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Traditional database investment logic focuses on:

• Data storage and management capabilities
• Query performance optimization
• Operation and maintenance automation

The AI era requires:

• Real-time data stream processing
  : Supports large-scale concurrent queries
• Vector search capabilities
  : Supports large model Retrieval-Augmented Generation (RAG)
• ML/AI native integration
  : Built-in machine learning workflows
• Observability
  : Monitors the output quality of AI models

ClickHouse’s acquisition of Langfuse is a reflection of this trend —

[1].

The market is forming two major camps:

Open Ecosystem Camp	Closed Platform Camp
ClickHouse (supports PostgreSQL)	Snowflake (proprietary format)
Databricks (embraces Iceberg)	Some traditional data warehouses
Apache Iceberg/Hudi	Vendor lock-in strategy

The impact of this trend on investments is:

, while closed platforms may face the risk of market share loss.

According to Fortune Business Insights, the global data analytics market was valued at approximately

in 2024, and is expected to reach by 2032, with a [4].

Real-time analytics will become the fastest-growing segment, which is highly aligned with the strategic direction of companies focusing on real-time processing such as ClickHouse and Databricks.

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The large-scale financings of ClickHouse and Databricks have validated the capital market’s long-term optimism about

. It is recommended that investors focus on:

• Database companies with real-time processing capabilities
• Enterprises with vector search and AI-native functions
• Companies with clear layouts in multi-cloud and open ecosystems

Despite the broad industry prospects, investors need to be alert to:

• Valuations in the private market may be overly optimistic
• There is a transmission lag in valuations between the primary and secondary markets
• Verification of profitability still takes time

Sub-Segment	Leading Company	Investment Logic
Cloud Data Warehouse	Snowflake	Multi-cloud ecosystem, network effects
Unified Data Lakehouse	Databricks	AI-native, Lakehouse architecture
Observability	Datadog	Unified monitoring, AI operations and maintenance
Real-Time Analytics	ClickHouse	High performance, developer-friendly
NoSQL	MongoDB	Flexible schema, AI vector search

Risk Type	Specific Performance	Impact Assessment
Macroeconomy	High interest rate environment suppresses valuations of growth stocks	Medium-term impact
Intensified Competition	Cloud vendors (AWS, Azure, GCP) continue to cut prices	Profit margin pressure
Technological Iteration	New architectures disrupt the existing pattern	Long-term risk
Regulatory Risk	Data privacy regulations become stricter	Increase in compliance costs
Liquidity	High dependence on private fundraising	Valuation volatility

• Long-term investors
  : May consider positioning in listed leaders such as Snowflake and Datadog during valuation corrections to benefit from industry integration dividends
• High-risk appetite investors
  : May follow the subsequent financing and IPO progress of unlisted enterprises such as ClickHouse
• Portfolio allocation
  : It is recommended to diversify allocations within the data infrastructure sector to balance growth and certainty

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ClickHouse’s $15 billion valuation is

, reflecting the capital market’s recognition of the following trends:

1. Real-time data processing
   has become a core competitiveness in the AI era
2. High growth (>100% ARR)
   can support high valuation multiples
3. Open ecosystems
   are defeating closed platforms
4. Valuation divergence between primary and secondary markets
   requires time to digest

For listed companies such as Snowflake and Datadog, ClickHouse’s high valuation is both a

and a — the reference frame represents the upper limit of valuations the market is willing to give for similar business models, while the catalyst represents the potential capital inflows brought by increased industry enthusiasm.

Ultimately,

will be the key to determining whether valuations can continue to expand. It is recommended that investors pay close attention to upcoming earnings reports (Snowflake on February 25, Datadog on February 12) to track the actual driving effect of AI functions on revenue growth[5][6].

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[1] MLQ.ai - ClickHouse Raises $400M Series D (https://mlq.ai/news/clickhouse-raises-400m-series-d-led-by-dragoneer-to-accelerate-expansion-across-analytics-and-ai-infrastructure/)

[2] TechCrunch - Snowflake, Databricks challenger ClickHouse hits $15B valuation (https://techcrunch.com/2026/01/16/snowflake-databricks-challenger-clickhouse-hits-15b-valuation/)

[3] AITNT News - Databricks Completes $4 Billion Financing, Valued at $134 Billion (https://m.aitntnews.com/newDetail.html?newId=20975)

[4] Fortune Business Insights - Data Analytics Market Size Report 2032 (https://www.fortunebusinessinsights.com/zh/data-analytics-market-108882)

[5] Jinling API - Snowflake Company Profile and Real-Time Quotation Data

[6] Jinling API - Datadog Company Profile and Real-Time Quotation Data

[7] Jinling API - MongoDB Company Profile and Real-Time Quotation Data

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Report Generation Date: January 17, 2026

Disclaimer: This report is for investment reference only and does not constitute specific investment advice. Investment involves risks; please proceed with caution.