Question 1

What is the main difference between HyperObserve and Datadog?

Accepted Answer

The fundamental difference is that HyperObserve uses eBPF technology for zero-instrumentation monitoring, while Datadog requires installing agents and SDKs in every application. This means HyperObserve can monitor your entire stack without any code changes, deployment restarts, or performance overhead (less than 2% CPU vs Datadog's 5-15%), while Datadog requires weeks of instrumentation work and significantly impacts application performance.

Question 2

Why is HyperObserve better than Datadog for monitoring?

Accepted Answer

HyperObserve is better than Datadog in several key ways: 1) Zero code changes required vs Datadog's extensive SDK integration, 2) 10x lower performance overhead (<2% CPU vs 5-15%), 3) 5-minute deployment vs weeks of setup, 4) 60% lower cost with predictable pricing vs Datadog's complex billing, 5) Language-agnostic monitoring vs Datadog's SDK limitations, 6) No vendor lock-in with your data vs Datadog's proprietary format.

Question 3

How much cheaper is HyperObserve compared to Datadog?

Accepted Answer

HyperObserve is 60-90% cheaper than Datadog depending on your usage. While Datadog charges $155/host/month plus additional fees for logs, APM, and custom metrics, HyperObserve's Pro plan is $99/host/month with everything included. For a 50-host infrastructure, you'd pay $7,750/month with Datadog vs $4,950/month with HyperObserve, saving $33,600 annually. Plus, no surprise bills from metric explosions or data ingestion overages.

Question 4

Can HyperObserve replace Datadog completely?

Accepted Answer

Yes, HyperObserve can completely replace Datadog for most use cases. It provides APM, infrastructure monitoring, database monitoring, distributed tracing, real-time alerting, and custom dashboards - all without code instrumentation. HyperObserve actually provides deeper visibility in some areas (kernel-level metrics, system calls, network packets) that Datadog's application-level agents cannot access. We provide free migration assistance to help you switch from Datadog.

Question 5

What is the performance impact of HyperObserve vs Datadog?

Accepted Answer

HyperObserve has dramatically lower performance impact than Datadog. HyperObserve uses less than 2% CPU overhead because eBPF programs run efficiently in kernel space with JIT compilation. Datadog agents typically consume 5-15% CPU overhead because they inject instrumentation code directly into your applications, plus additional memory for buffering and network overhead for constant data transmission.

Question 6

How long does it take to implement HyperObserve vs Datadog?

Accepted Answer

HyperObserve takes 5 minutes to deploy versus weeks or months for Datadog. With HyperObserve, you simply run a single Docker command or apply a Kubernetes YAML file, and you immediately get full visibility. Datadog requires installing agents on every host, adding SDKs to every application, instrumenting code, configuring collectors, setting up dashboards, and testing - a process that typically takes 2-6 weeks for full implementation.

Question 7

Does HyperObserve work with all programming languages unlike Datadog?

Accepted Answer

Yes, HyperObserve works with ALL programming languages and frameworks because it operates at the kernel level, not the application level. It can monitor Go, Java, Python, Node.js, C++, Rust, .NET, PHP, Ruby, and any other language without requiring language-specific SDKs. Datadog is limited to languages that have SDK support and requires different instrumentation approaches for each language, often missing newer languages or frameworks.

Question 8

Why is Datadog so expensive compared to HyperObserve?

Accepted Answer

Datadog is expensive due to its complex pricing model with separate charges for infrastructure ($15/host), APM ($40/host), logs ($1.70/GB), RUM ($1.20/1000 sessions), synthetics, and custom metrics. A typical setup costs $155-300/host/month. HyperObserve includes everything in one price: $99/host/month for Pro with unlimited metrics, logs, traces, and alerts. Datadog also has unpredictable billing from metric explosions and data ingestion spikes.

Question 9

What are the hidden costs of Datadog vs HyperObserve?

Accepted Answer

Datadog has many hidden costs that HyperObserve doesn't: 1) Custom metrics overage fees, 2) Log ingestion charges, 3) Data retention costs, 4) Additional host charges for auto-scaling, 5) Premium integrations, 6) Professional services for setup. HyperObserve has transparent, predictable pricing with no overages, no data ingestion fees, and includes migration assistance. You also save on infrastructure costs due to our 10x lower CPU overhead.

Question 10

Is there a free tier for HyperObserve like Datadog?

Accepted Answer

Yes, HyperObserve offers a more generous free tier than Datadog. HyperObserve's free tier includes up to 5 hosts with full APM, infrastructure monitoring, distributed tracing, and 7-day data retention. Datadog's free tier only covers 5 hosts for infrastructure monitoring with limited features and 1-day retention. HyperObserve's free tier gives you the complete platform to evaluate, while Datadog's free tier is very limited.

Question 11

How does HyperObserve's database monitoring compare to Datadog?

Accepted Answer

HyperObserve provides superior database monitoring compared to Datadog. HyperObserve monitors 11+ databases (MySQL, PostgreSQL, MongoDB, Redis, Oracle, SQL Server, etc.) without requiring database credentials or extensions, using eBPF to capture database protocol traffic. Datadog requires installing separate database agents, managing credentials, and often needs database extensions or plugins. HyperObserve captures query performance, connection pools, and resource usage automatically.

Question 12

Can HyperObserve do distributed tracing like Datadog APM?

Accepted Answer

Yes, HyperObserve provides distributed tracing that's superior to Datadog APM. HyperObserve automatically traces requests across all services without any code instrumentation, capturing complete request flows through microservices, databases, and external APIs. Datadog requires installing APM agents in every service and instrumenting code with their SDKs. HyperObserve's tracing captures kernel-level details that Datadog misses, providing deeper insights into service communications.

Question 13

Does HyperObserve work with Kubernetes better than Datadog?

Accepted Answer

Yes, HyperObserve is designed specifically for cloud-native environments and works better with Kubernetes than Datadog. HyperObserve deploys as a simple DaemonSet without requiring sidecars, admission webhooks, or service mesh modifications. It automatically monitors all pods, services, and network traffic. Datadog requires the Datadog Agent DaemonSet plus additional sidecars for some features, creating more complexity and resource overhead in your Kubernetes clusters.

Question 14

How do I migrate from Datadog to HyperObserve?

Accepted Answer

Migrating from Datadog to HyperObserve is straightforward and risk-free: 1) Install HyperObserve alongside your existing Datadog setup (no conflicts), 2) Verify HyperObserve captures all your metrics and traces over 1-2 weeks, 3) Use our migration tools to recreate Datadog dashboards and alerts in HyperObserve, 4) Remove Datadog agents to immediately reduce CPU usage and costs. We provide free migration assistance for Pro and Enterprise customers, including dashboard recreation and team training.

Question 15

Can I run HyperObserve and Datadog at the same time?

Accepted Answer

Yes, you can safely run HyperObserve and Datadog simultaneously during your evaluation period. Since HyperObserve operates at the kernel level without touching your applications, it won't interfere with Datadog agents. This allows you to compare metrics, validate coverage, and ensure HyperObserve meets all your monitoring needs before removing Datadog. Many customers run both for 1-2 weeks during migration to ensure a smooth transition.

Question 16

What support does HyperObserve provide for switching from Datadog?

Accepted Answer

HyperObserve provides comprehensive migration support to make switching from Datadog seamless: 1) Free migration consultation to assess your current Datadog setup, 2) Automated tools to recreate Datadog dashboards in HyperObserve, 3) Alert configuration assistance to match your existing Datadog alerts, 4) Team training sessions on HyperObserve features, 5) Dedicated support during the transition period. Our goal is to make the switch effortless while improving your monitoring capabilities.

Feature	HyperObserve	Datadog
Implementation	Zero code changes, eBPF-based	Requires SDK integration in every service
Performance Overhead	Less than 5% CPU overhead	5-15% CPU overhead from agents
Time to Deploy	5 minutes, no restarts	Days to weeks for full implementation
Pricing Model	Simple, predictable pricing	Complex pricing, unexpected bills
Data Ownership	Your data, your storage	Vendor lock-in, data in their cloud
Language Support	All languages, kernel-level	Limited to supported SDKs
Database Monitoring	11+ databases including Oracle, MySQL, PostgreSQL, MongoDB, Redis, SQL Server - zero config	Requires separate agents
Kubernetes Monitoring	No sidecars needed	DaemonSet + sidecars required
Real User Monitoring	Lightweight RUM included	Separate RUM product
Service Mesh Monitoring	Native Istio, Envoy, Consul, Linkerd support without sidecars	Requires additional configuration
ML & Predictive Analytics	Time series forecasting, failure prediction (30-min advance), capacity planning	ML-based insights and anomaly detection
Security & Vulnerability Management	CVE tracking, hardware health, SSL cert monitoring, MITRE ATT&CK	Security monitoring and compliance
Open Source	Core is open source	Proprietary, closed source

HyperObserve vs Datadog

Key Differences at a Glance

Implementation

Performance

Pricing

Feature-by-Feature Comparison

Pricing Comparison

HyperObserve

Starter

Pro

Enterprise

Datadog

Infrastructure

Full Stack

Enterprise

Common Datadog Pricing Issues

Technical Architecture Comparison

HyperObserve: eBPF-Based

Kernel-Level Monitoring

No Code Changes

Minimal Overhead

Datadog: Agent-Based

Application-Level Agents

Code Instrumentation

High Overhead

Switching from Datadog to HyperObserve

Install HyperObserve (5 minutes)

Run Side-by-Side (1 week)

Migrate Dashboards & Alerts

Remove Datadog Agents

Migration Support Included

Why Teams Switch from Datadog

Frequently Asked Questions