The Forrester Wave™: AIOps Platforms, Q2 2025

AIOps Platforms Vendor Product Comparisons 2025

Key features and pros and cons of top AIOps Platforms products:

Datadog - Leaders

Pros:

Superior data governance and lineage positions Datadog well for continued growth
Observability Graph to map relationships between services
Platform discovers and provides real-time visibility while detecting trends, anomalies, and correlating issues to reduce noise
Commitment to constantly identify the next most important requested capability
Strong partnerships grant clients access to product owners

Cons:

Bits AI needs enhancements to implement and deploy proactive capabilities
Data can be overwhelming for new users to find what they are looking for
Roadmap lacks detailed timeline for expansion of AI/ML capabilities

Dynatrace - Leaders

Pros:

Davis AI engine delivers precise root cause analysis and automated remediation
OneAgent auto-updates, self-configures, and autodiscovers and instruments technologies dynamically
Davis AI processes data in near real time to detect anomalies, correlate with topologies, and identify root causes
OpenPipeline designed for enterprise scale with minimal maintenance
Superior vision builds upon OpenPipeline and Grail

Cons:

As transition to Grail continues, some capabilities can feel disjointed
Upskilling users and transitioning them from primitive single-minded view to multifaceted understanding is a challenge
Users need improved UX to ensure ease of use

ScienceLogic - Leaders

Pros:

SL1 platform and Skylar AI excel in anomaly and root cause detection and agentic AI capabilities
Pulling in telemetry from cloud, infrastructure, and connected devices enables superior intelligent and suggestive alerting
Bring-your-own business intelligence tool enables clients to maximize value from investments
Customers excited about new architecture and predictive analytics that Skylar brings
Powerpacks deliver flexibility and extensibility

Cons:

Dependency on third-party APM puts it at a disadvantage with peers
Lack of native APM offering poses challenge for customers seeking tool consolidation and IT simplification
Customers servicing their clients find challenges with regards to upgrades and backward compatibility

BMC Software - Strong Performers

Pros:

Excels in creating service maps that inform and drive intelligent and suggestive alerting capability
BMC Helix Edge features extend intelligence to connected devices on the edge
Ability to bring discovery and event management together with ITSM support
Superior service mapping capability
Concerted multiyear effort to build AI-driven platform with genAI and RAG throughout

Cons:

Permission-based access can be too regimented at times, requiring engineering teams to be engaged
Customers want BMC to invest more in training to help customers be successful
Must determine how to further elevate itself in ITSM and AIOps markets simultaneously to close in on market leaders

Splunk - Strong Performers

Pros:

Superior digital experience monitoring includes natively supporting web and mobile apps as well as hybrid frameworks
Strong native capabilities draw insights from telemetry collected from networks, connected devices, and logs
Superior partner ecosystem for transparency, certifications, and public pricing
Way content is served is very useful and helps uplevel skills of junior-level operators
Flexibility to get data from various sources and facilitate use by different personas

Cons:

Integration between AppDynamics and Splunk ITSI is still building deep links for complete visibility across entire hybrid environment
Adoption during acquisition period is difficult as organizations hold off on long-term decisions
Can take a lot of effort to keep configurations and instrumentations up to date
Customers expressed concern about how Cisco and Splunk cultures will meld

OpenText - Strong Performers

Pros:

Excels with ability to model and manage IoT devices, including their components and relationships
Superior data-driven automation and remediation abilities
Differentiated AI model development and monitoring capability
APIs allow third-party solutions to exchange events and data
Automation capabilities saved tremendous amounts of manpower and money (approximately 70% of incident tickets closed, 75% auto-remediated)

Cons:

Ability to share reports created ad hoc is uniquely useful, but more investment needed to ease flow of information for intelligent and suggestive alerting
Documentation has been a big downfall, driving OpenText to rewrite some of it
Pricing model not posted on website and difficult to assess with partners
Should update messaging to speak more clearly about business impact and contextualization

ServiceNow - Strong Performers

Pros:

Superior roadmap based on long-term strategy to enhance predictive capabilities, automate processes, and further leverage AI for decision-making
Data governance and lineage combine with service map creation and Service Graph Connector to provide expansive view of IT estate
Ease of interacting with other tools
Ability to configure groupings, correlations, and sending incidents very quickly
Setup and configuration seen as easy

Cons:

Below-par capabilities often in areas rooted in monitoring or APM, less likely in areas where ITSM is dominant driver
Pricing model and packages lack public pricing details
Decision to keep Cloud Observability (formerly Lightstep) as separate product not being well received
Innovation and automation focus not differentiating

Elastic - Contenders

Pros:

Data discovery and processing is a solid capability
Contextualizing volumes of data enables Elastic Search to be used as a data platform
OneAgent approach allows quick retrieval of log data and is managed centrally
Log management capabilities help identify potential problems
Customers appreciate simplicity of Elastic Agent

Cons:

Lack of guidance or automation for regularly performed tasks wastes user time
Investments in AI agents are starting to deliver value but still need more maturing
Search versus monitoring approach is unique and requires experienced individual who knows Elastic Search well to configure and tune deployment
More refinement needed to fully capitalize on AI and genAI technologies

New Relic - Contenders

Pros:

Real-time APM with comprehensive view across systems is a core strength
Superior support for IT optimization and digital employee experience
New Relic Query Language (NRQL) praised for its power
Lower price point compared to larger peers
Reliable platform that enables extensive use of open-source tooling such as Prometheus and OpenTelemetry

Cons:

Learning curve to utilize features and extract full value
Needs to improve how it delivers telemetry and facilitates consumption for less technical users doing anomaly and root cause detection or incident detection and mitigation
Roadmap lacks detailed timelines
Innovation is not differentiated
Partner program lacks specificity regarding certifications
Platform usability still challenging - must do more to improve ease of use for non-engineers
NRQL is not trivial and needs lots of skill and time to learn

PagerDuty - Contenders

Pros:

Strength in ability to process data at rest and data in motion through event ingestion and orchestration from over 700 integrations
Strong data-driven automation and remediation capabilities once data has been ingested
AI model governance, alignment development, and monitoring bolster data governance and lineage strength
Easily customized
Vendor is transparent about what is and isn't in the platform
Event orchestration is highly regarded
Industry-recognized on-call capabilities
Superior adoption with one of highest net revenue retention rates in evaluation

Cons:

Lack of native monitoring and observability capability limits ability to shape data at device level
IT simplification and technology sprawl initiatives hampered without option to eliminate redundant monitoring tools
Vision is that of operational enrichment tool that uses AI but lacks native observability or monitoring
Integrations with tools such as Teams, Atlassian, and Slack have garnered mixed reviews

FAQs

Q: Which vendors are Leaders in 2025?

A: Datadog, Dynatrace, ScienceLogic

Q: What does "Leader" mean in Forrester Wave terms?

A: Leaders in the Forrester Wave have the highest combined scores for current offering and strategy. Leaders demonstrate strong vision, innovation, and execution across the evaluation criteria. In the context of AIOps Platforms, Leaders excel at delivering comprehensive native telemetry access, tailoring insights to diverse personas, and enabling both additive and discrete implementation approaches. They show superior capabilities in areas such as data governance, service mapping, AI-driven analytics, anomaly detection, and automated remediation while maintaining a clear strategic roadmap for future innovation.

Q: How do I interpret a Forrester Wave?

A: https://www.forrester.com/policies/forrester-wave-methodology/

Report:

Top Vendor Products for AIOps Platforms in 2025

AIOps Platforms Vendor Product Comparisons 2025

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FAQs

Q: Which vendors are Leaders in 2025?

Q: What does "Leader" mean in Forrester Wave terms?

Q: How do I interpret a Forrester Wave?

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