Top 5 Splunk Alternatives in 2025

When it comes to log analysis, observability, and security intelligence, Splunk has long been considered the industry heavyweight. From large enterprises to lean DevOps teams, Splunk powers mission-critical insights by transforming massive volumes of machine-generated data into real-time dashboards, alerts, and threat detections. Its flexible query language, robust visualization tools, and broad ecosystem make it a compelling solution for IT operations, cybersecurity, and compliance alike.

But even with its powerful capabilities, Splunk isn’t a perfect fit for everyone—especially in 2025.

As engineering teams scale up cloud infrastructure, adopt microservices, and lean into AI and machine learning, they’re finding that Splunk’s high cost, operational complexity, and vendor lock-in can become real obstacles. Modern observability isn’t just about having the most powerful features; it’s about choosing the right tool for your specific architecture, budget, and team.

In this article, we’ll highlight the top 5 Splunk alternatives in 2025, each bringing a unique approach to observability, log management, and security analytics. Whether you’re looking for a fully managed SaaS solution or an open-source system you can run on your own terms, you’ll find something worth exploring on this list.

What makes a good Splunk Alternative? #

Choosing the right alternative to Splunk depends on your organization’s scale, technical stack, and priorities—but several key qualities consistently define the best options.

Here’s what modern teams tend to look for in a Splunk alternative:

Cost Efficiency at Scale #

Many teams are struggling with the rising costs of observability. A good alternative offers transparent pricing, usage-based billing, or open-source flexibility that helps control costs without sacrificing performance. The industry has converged on per GB ingest pricing for most sub use cases, with additional charges for retention, allowing users to compare solutions easily. Modern solutions exploit high compression rates and object storage to offer long term retention without it dominating the overall TCO.

Cloud-Native or Hybrid Support #

With the move toward containers, serverless, and Kubernetes, tools that offer cloud-native telemetry ingestion, horizontal scalability, and native integrations with AWS, GCP, or Azure are in high demand.

Unified Telemetry #

The best alternatives go beyond logs, offering metrics, traces, and sometimes real user monitoring (RUM) in a single platform—allowing for holistic debugging and analysis without context switching. Advanced platforms address other sub-use cases such as LLM observability, profiling and database monitoring.

Open Standards and Ecosystem Flexibility #

Support for OpenTelemetry is becoming a baseline. Teams want to avoid vendor lock-in and maintain control over how they ingest and route telemetry data.

Built-in Intelligence and Automation #

Modern observability stacks are expected to do more than just collect data. Whether through AI-assisted anomaly detection, automated root cause analysis, or predictive alerts, intelligence is now part of the stack.

Security and Compliance Features #

As observability and security operations increasingly overlap, strong SIEM features, user behavior analytics (UEBA), and compliance reporting are key differentiators for teams handling sensitive workloads.

What are the alternatives to Splunk? #

Let’s take a closer look at five of the strongest Splunk alternatives in 2025!

ClickStack #

ClickStack is an open-source observability stack built on ClickHouse, designed from the ground up to support OpenTelemetry at scale. It delivers unmatched performance for logs, traces, and metrics—storing data at a fraction of the cost thanks to ClickHouse’s industry-leading compression and executing analytical queries in milliseconds for instant charting and search. Designed for Petabyte scale, ClickStack powers some of the world’s largest observability deployments.

ClickStack unifies all observability signals—logs, traces, and metrics—into a single, intuitive interface HyperDX. Inspired by tools like Chrome DevTools, it enables developers and SREs to replay sessions, trace requests across distributed systems, and debug issues in real time—all without leaving the browser. Beyond observability, ClickStack lets teams correlate OpenTelemetry data with business and product metrics stored in the same ClickHouse instance. Whether using a Lucene-like query syntax for quick filtering or SQL for deeper analysis, users can seamlessly explore relationships across operational and business dimensions.

Unlike traditional observability platforms that are complex, costly, and fragmented, ClickStack is developer-first, OpenTelemetry-native, and fully open source - with a hosted SaaS option for teams that want zero infrastructure overhead. It’s built for speed, simplicity, and insight at any scale.

Pros of ClickStack:

• OpenTelemetry-native: No vendor lock-in; supports open standards and popular SDKs. Designed for OpenTelemetry at scale with ClickHouse as the unified backend.
• Session-level context: Combines logs, traces, and metadata into a single flow for real-time issue investigation and faster root-cause analysis.
• Open source: Transparent architecture with the flexibility to self-host or use a fully managed SaaS deployment with zero infrastructure overhead.
• Official ClickHouse interface: Built and maintained by the ClickHouse team, ensuring native compatibility, optimized performance, and seamless integration with the broader ClickHouse ecosystem.
• Unified data store: Correlate observability data with business, analytics, or application metrics stored in the same ClickHouse instance—no need for multiple tools or pipelines.
• Blazing-fast analytics: Powered by ClickHouse’s columnar engine, ClickStack supports sub-second queries, real-time dashboards, and fast interactive searches across trillions of rows.
• Cost-efficient scalability: Benefit from ClickHouse’s industry-leading compression and efficient resource utilization, reducing storage and compute costs dramatically.
• Developer-first experience: Inspired by Chrome DevTools and modern debugging tools, offering a familiar, intuitive interface for engineers and SREs.

Cons of ClickStack

• Best of breed focus: ClickStack focuses primarily on logs, APM, and RUM with session replays and OpenTelemetry at scale. While other use cases can be supported by adapting data to OpenTelemetry formats, it doesn’t provide an out of the box experience for the broad set of observability sub use cases.
• No native profiling support: As of October 2025, ClickStack does not include profiling or flame graphs for low-level instrumentation and performance debugging.
• Nascent metrics capabilities: Metrics support is built on OpenTelemetry Metrics, with PromQL compatibility still maturing, making it less suitable for organizations heavily invested in Prometheus-based monitoring.
• No security analytics or SIEM functionality: ClickStack is focused solely on observability and does not aim to unify observability with security use cases such as threat detection, alert correlation, or incident response.
• Fewer prebuilt integrations: Compared to legacy observability platforms, ClickStack offers fewer out-of-the-box connectors and dashboards, requiring more manual configuration for specialized data sources.
• Smaller ecosystem maturity: As a newer open-source stack, ClickStack’s community and plugin ecosystem are growing but not yet as extensive as those of long-established commercial platforms.

What is ClickStack’s Pricing?

ClickStack can be deployed and self-managed at no cost using its open-source components. The HyperDX interface is released under the MIT license, while ClickHouse and the OpenTelemetry components are licensed under Apache 2.0, ensuring full transparency and flexibility for self-hosted deployments. For teams seeking a managed experience, ClickStack can be hosted on ClickHouse Cloud, where pricing is based on storage and compute consumption. This usage-based model allows teams to fine-tune performance and cost according to workload requirements.

Typical pricing starts around $160 per month, with storage costs averaging low cents per GB, offering one of the most cost-efficient observability solutions available.

Datadog #

Datadog is one of the most comprehensive observability platforms on the market, offering unified visibility across infrastructure, application performance, logs, security signals, and even real user monitoring (RUM). It’s a fully managed, cloud-native SaaS product that’s deeply integrated with more than 600 tools and platforms, from Kubernetes to AWS, PostgreSQL to Redis.

Datadog has evolved into the enterprise standard for full-stack observability, especially in teams that value deep integrations, out-of-the-box dashboards, and centralized alerting. It’s especially popular in DevOps and SRE environments where logs, metrics, and traces need to be correlated across complex microservice architectures.

That said, Datadog’s scope comes at a cost. While it excels in many aspects, its pricing model can be challenging to manage, particularly as data volumes scale.

Pros:

• All-in-one platform: Combines logs, metrics, traces, security, APM, and RUM into a single product suite.
• Extensive integrations: 600+ native integrations make setup fast across most modern tech stacks.
• Powerful dashboards and alerting: Out-of-the-box visualizations with customizable alerts and SLO tracking.
• AI-driven observability: Features like Watchdog and Bits AI help detect anomalies and suggest root causes.
• Highly scalable: Proven performance in large, global deployments with complex architectures.

Cons:

• Expensive at scale: Pricing can quickly balloon with high log ingestion or usage across multiple products.
• Overkill for smaller teams: Many features may go unused in startups or simple architectures.
• Learning curve: Requires onboarding and tuning to make full use of its capabilities and avoid data sprawl.

Pricing:

Datadog offers 5 different tiers, each tier being an upgrade of the previous. They start off with a free basic-tier, that allows 5 day retention and is for up to 5 users. From there on they offer a pro-tier for $15/host/month, an enterprise-tier retailing at $23/host/month, and DevSecOps pro and enterprise tiers beginning at $22 and $34/host/month respectively.

New Relic #

New Relic is a full-stack observability platform designed to give engineering teams a single pane of glass across logs, metrics, traces, browser monitoring, and infrastructure. It pioneered APM in the early 2010s and has since evolved into a more holistic platform, with a unified telemetry database and a powerful query language (NRQL) at its core.

Unlike some competitors, New Relic combines multiple data types into a single telemetry pipeline, enabling fast, correlation-rich debugging and alerting. It’s especially popular with frontend and full-stack teams who benefit from built-in support for real user monitoring (RUM), mobile observability, and browser session data—all layered on top of backend traces and logs.

Pros:

• Unified telemetry database: Logs, metrics, traces, browser, and mobile data all live in one queryable layer.
• Fast and flexible querying: NRQL enables granular analysis, dashboarding, and alert logic.
• Developer-friendly pricing: Usage-based model with generous free tier and predictable costs.
• Simplified onboarding: Fast agent setup and built-in integrations for popular languages and platforms.

Cons:

• Limited security features: No native SIEM functionality or threat detection modules.
• Learning curve with NRQL: Custom query language requires familiarity to unlock full value.
• Lower depth in infra monitoring: Compared to Datadog, lacks some detail in infrastructure metrics.
• Not ideal for large-scale log retention: Cost and performance may not scale as well for massive datasets.

Pricing:

New Relic offers a free tier, paid tiers are based on a mix of users (starting at $99/full user) and data (starting at $0.35/GB)

Chronosphere #

Chronosphere is a cloud-native observability platform purpose-built for teams operating large-scale, containerized environments. It’s designed to handle the challenges of high-cardinality, high-volume telemetry data without breaking performance or budgets.

Whereas traditional observability platforms focus on collecting everything and figuring it out later, Chronosphere flips the model by giving teams control over what data gets ingested, stored, and visualized. This makes it especially appealing for organizations struggling with the rising cost and noise of observability in microservice-heavy architectures.

Chronosphere is best known for its metric-first approach, but has recently expanded to support distributed tracing and logging pipelines. It emphasizes performance and cost efficiency, with tooling designed to help teams fine-tune telemetry workflows and reduce unnecessary data before it hits storage. While it may lack the polish and surface-area coverage of platforms like Datadog or New Relic, it shines in environments that demand scale, precision, and control.

Pros:

• Built for Kubernetes and microservices: Designed for modern, distributed systems with native K8s and Prometheus support.
• Cost optimization tooling: Helps reduce telemetry costs by filtering, transforming, or dropping unneeded data.
• High performance at scale: Efficient ingestion and querying for high-cardinality data sets.
• Strong enterprise adoption: Used by scale-heavy teams like Snap, DoorDash, and Zillow.

Cons:

• No self-hosted option: SaaS only, which may not suit compliance-heavy orgs.
• Limited security tooling: Not designed for SIEM or threat detection use cases.
• Smaller integration ecosystem: Fewer native connectors than tools like Datadog.
• Targeted at advanced teams: Best suited for orgs with mature observability practices; may be overkill for simpler setups.

Pricing:

Chronosphere observability platform offers a rather unique pricing model. They charge based on “useful” data that a customer decides to retain on their platform. For Chronosphere Telemetry pipeline, they charge based on the volume of data transmitted through the pipeline.

Sumo Logic #

Sumo Logic is a cloud-native machine data analytics platform focused on log management, real-time monitoring, and security insights. It positions itself as a centralized hub for DevOps, SecOps, and ITOps teams to ingest and analyze large volumes of structured and unstructured telemetry data — all without managing infrastructure.

Unlike tools that evolved from APM or developer-first observability, Sumo Logic stands out for its mature SIEM capabilities, parquet-based performance, and multi-tenant architecture designed for scale. It’s used heavily in industries with strict compliance requirements and security operations teams that want both observability and threat detection under one roof.

Sumo Logic isn’t the flashiest platform, but it has deep operational chops and enterprise credibility. It’s a particularly strong Splunk alternative for teams that want strong security tooling, real-time log analytics, and fast time-to-value without managing a DIY stack.

Pros:

• Cloud-native architecture: No infrastructure management; elastic scaling for high-ingestion workloads.
• Integrated Cloud SIEM: Built-in threat detection, user behavior analytics (UEBA), and compliance content.
• Real-time dashboards: Powerful log analytics with live streaming visualizations and alerting.
• Wide format support: Handles structured, unstructured, and semi-structured logs well.
• OpenTelemetry support: Enables integration across modern observability pipelines.

Cons:

• Less developer-friendly: UI and onboarding are more suited to Ops and SecOps teams than app developers.
• UI can feel dated: Compared to Datadog or ClickStack’s HyperDX UI, the interface feels less modern and intuitive.
• Expensive at high volumes: Pricing can escalate with increased ingestion, especially in log-heavy environments.
• Limited APM features: Not as comprehensive in tracing and code-level performance analysis.

Pricing:

SumoLogic doesn’t offer visible pricing, however from what can be publicly seen, they offer 3 tiers ranging from an essentials-tier to an enterprise-tier. They also offer a new tier for customers called “flex”, where the customer pays only for analytics and insights.

Conclusion #

Splunk remains a powerhouse in the observability and security space, but in 2025, it's clear that the market has grown far beyond a one-size-fits-all solution. Whether you're a fast-moving startup trying to reduce observability costs or an enterprise looking to optimize performance across a massive cloud footprint, there's likely a better-fit alternative available.

From Datadog’s enterprise-grade full-stack visibility, to New Relic’s unified telemetry and developer-friendliness, to Chronosphere’s precision-first, Kubernetes-native design, the options are both diverse and specialized. Meanwhile, tools like ClickStack are reimagining observability from the developer’s perspective with open source offerings, and Sumo Logic continues to offer robust security and SIEM capabilities for compliance-heavy teams.

Ultimately, the best Splunk alternative comes down to your team’s priorities — whether it’s cost control, performance at scale, self-hosting, or simplified debugging. As the observability space continues to mature, choosing the right tool is less about finding a replacement for Splunk and more about aligning with a platform that matches your workflow, stack, and scale.