This article is based on a piece originally published at Motley Fool (fool.com) in April 2020. Financial figures and forecasts reflect conditions as of that date and should not be used for current investment decisions.
The Case for Growth Stocks in a Volatile Market
When equity markets become volatile, investors face a recurring dilemma: retreat into large-cap dividend payers with proven balance sheets, or stay committed to high-growth companies that can deliver outsized long-term returns? The argument for growth stocks is straightforward — while they experience sharper drawdowns during downturns, they have historically created substantial wealth for patient investors.
In the observability and data monitoring space, Splunk (NASDAQ: SPLK) had long been considered the benchmark. Its enterprise platform for big data search, monitoring, and analytics became a standard tool in IT operations. But by early 2020, a newer entrant — Datadog (NASDAQ: DDOG) — was growing faster and building a more modern, cloud-native product portfolio.
What Does Datadog Actually Do?
Datadog is a SaaS-based monitoring and analytics platform designed for modern, cloud-scale infrastructure. Unlike legacy monitoring tools, it was built from the ground up to handle dynamic, containerised, and microservices-based architectures. Its platform integrates three historically separate disciplines into a single unified interface:
- Infrastructure Monitoring — visibility into hosts, containers, serverless functions, and cloud services across AWS, Azure, GCP, and hybrid environments.
- Application Performance Monitoring (APM) — distributed tracing and service dependency mapping for modern applications.
- Log Management — centralised log ingestion, indexing, and analysis correlated with metrics and traces.
Datadog’s product timeline reflects a deliberate expansion strategy:
- 2012: Infrastructure monitoring platform launched to address cloud-native architectures.
- 2017: APM product introduced, enabling end-to-end request tracing.
- 2018: Log management added to close the observability loop.
- 2019: User experience monitoring, network performance monitoring, and security monitoring joined the platform.
The result is an end-to-end observability platform that is cloud-agnostic — meaning it works consistently across multi-cloud and hybrid environments without locking customers into a single provider.
Datadog’s Addressable Market
Datadog’s platform targets the IT operations management market. According to Gartner estimates cited at the time of the original article, this market represented a $37 billion addressable opportunity. With annual revenue of approximately $363 million in 2019, Datadog held less than 1% of that market — leaving substantial runway for growth over the following decade.
Key Growth Metrics (FY2019)
Datadog’s financial and operational metrics for 2019 painted a picture of rapid, compounding growth:
- Revenue growth: 85% year-over-year in Q4 2019.
- Total customers: 10,500 at end of 2019, up from 7,700 in 2018.
- Enterprise customers (ARR > $100K): 858, representing 89% year-over-year growth.
- Average enterprise ARR: Grew from $160,000 (2018) to $230,000 (2019).
- Average mid-market ARR: Grew from $110,000 (2018) to $170,000 (2019).
- Net retention rate: 130%, driven by customers adopting additional products.
- Multi-product adoption: Over 60% of customers using two or more products.
- Operating cash flow: $24.2 million in 2019, up from $10.8 million in 2018.
- Cash balance: $778 million at year-end, providing strong liquidity.
The 130% net retention rate is particularly significant from a product perspective. It means that, on average, existing customers were spending 30% more year-over-year — a sign that Datadog’s platform strategy of cross-selling additional modules was working in practice.
2020 Guidance (as of April 2020)
At the time of the original article, Datadog had issued the following guidance:
- Q1 2020: Revenue of $117–119 million, implying approximately 68.5% year-over-year growth at the midpoint.
- Full-year 2020: Revenue of $535–545 million, implying approximately 49% year-over-year growth.
These projections carried a caveat: the COVID-19 pandemic introduced significant uncertainty around enterprise IT spending. The article acknowledged that guidance could be revised downward as the macroeconomic picture became clearer.
Datadog vs. Splunk: Valuation and Growth Trade-Off
At the time of writing (April 2020), Datadog traded at a market-cap-to-forward-sales ratio of approximately 22.6x, compared to Splunk’s 8.4x. The premium valuation reflected Datadog’s significantly higher revenue growth rate.
Splunk remained a well-established, valuable platform — particularly for security information and event management (SIEM) and enterprise log analytics. However, the argument presented was not that Splunk was a poor business, but that Datadog’s growth trajectory, cloud-native architecture, and expanding product footprint made it a more compelling growth story at that stage of its development.
Why the Platform Approach Matters Technically
From an engineering perspective, Datadog’s integrated platform addresses a real operational pain point: tool sprawl. Historically, teams used separate tools for metrics, logs, and traces — each with its own interface, query language, and data model. Correlating an application slowdown across these three pillars required manual effort and context-switching.
Datadog’s unified data model allows engineers to move seamlessly between a host-level metric anomaly, the associated application traces, and the underlying logs — all within a single platform. This reduces mean time to resolution (MTTR) and lowers the operational burden on SRE and DevOps teams.
Its cloud-agnostic integrations — covering over 450 technologies at the time — also meant that organisations running workloads across AWS, Azure, and GCP did not need to deploy separate monitoring stacks per cloud.
Important Caveats for Readers
This article summarises analysis from April 2020. The financial figures, valuations, customer counts, and competitive dynamics described here are historical. Datadog, Splunk, and the broader observability market have evolved considerably since then. This content should not be interpreted as current investment advice. Always verify figures against the most recent company filings and consult a qualified financial adviser before making investment decisions.