Best Observability Tools for Snowflake
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Compare the Top Observability Tools that integrate with Snowflake as of October 2025
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This a list of Observability tools that integrate with Snowflake. Use the filters on the left to add additional filters for products that have integrations with Snowflake. View the products that work with Snowflake in the table below.
What are Observability Tools for Snowflake?
Observability tools are software platforms that help monitor, measure, and gain insights into the performance and health of systems, applications, and infrastructure. These tools provide a comprehensive view of the system by collecting and analyzing data from various sources, including logs, metrics, traces, and events. Observability tools are essential for identifying and diagnosing issues, improving system reliability, and optimizing performance. They enable real-time monitoring, anomaly detection, root cause analysis, and alerting, which allows teams to respond proactively to potential problems. By offering detailed insights into system behavior, observability tools are critical for DevOps, cloud-native environments, and microservices architectures. Compare and read user reviews of the best Observability tools for Snowflake currently available using the table below. This list is updated regularly.
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1
Datadog
Datadog
Datadog is the monitoring, security and analytics platform for developers, IT operations teams, security engineers and business users in the cloud age. Our SaaS platform integrates and automates infrastructure monitoring, application performance monitoring and log management to provide unified, real-time observability of our customers' entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior and track key business metrics.Starting Price: $15.00/host/month -
2
Sifflet
Sifflet
Automatically cover thousands of tables with ML-based anomaly detection and 50+ custom metrics. Comprehensive data and metadata monitoring. Exhaustive mapping of all dependencies between assets, from ingestion to BI. Enhanced productivity and collaboration between data engineers and data consumers. Sifflet seamlessly integrates into your data sources and preferred tools and can run on AWS, Google Cloud Platform, and Microsoft Azure. Keep an eye on the health of your data and alert the team when quality criteria aren’t met. Set up in a few clicks the fundamental coverage of all your tables. Configure the frequency of runs, their criticality, and even customized notifications at the same time. Leverage ML-based rules to detect any anomaly in your data. No need for an initial configuration. A unique model for each rule learns from historical data and from user feedback. Complement the automated rules with a library of 50+ templates that can be applied to any asset. -
3
Observe
Observe
Observe – the AI-powered observability company – is reinventing how businesses detect anomalies, troubleshoot applications, and resolve incidents to deliver exceptional customer experiences. Only Observe eliminates silos of logs, metrics, and traces by storing all data in a single, cost-efficient data lake, analyzing all telemetry data using a single language, and providing access through a single, consistent, user interface. Observe’s AI-Powered Observability enables companies to resolve software incidents three times faster at one-third the cost. Customers such as Capital One, Dialpad AI, Top Golf and more trust Observe to turn their data into actionable insights.Starting Price: $0.35 Per GiB -
4
Edge Delta
Edge Delta
Edge Delta is a new way to do observability that helps developers and operations teams monitor datasets and create telemetry pipelines. We process your log data as it's created and give you the freedom to route it anywhere. Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source. We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost. By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment.Starting Price: $0.20 per GB -
5
LOGIQ
LOGIQ.AI
LOGIQ.AI’s LogFlow provides centralized control of your observability data pipelines. As data streams arrive, they are automatically organized and optimized for your business teams and knowledge workers. XOps teams can centralize data flow management, gain data EPS control, and increase data quality and relevance. Built on any object store, LogFlow’s InstaStore enables infinite data retention and on-demand data replay to any target observability platform of your choice. Analyze operational metrics across applications and infrastructure and gain actionable insights that help you scale with confidence while maintaining high availability. Fuel business decisions and better user experiences by collecting, transforming, and analyzing behavioral data and usage patterns from business systems. Don’t let new attack techniques catch you off guard. Detect and analyze threat patterns from multiple sources and automate threat prevention and remediation. -
6
Bigeye
Bigeye
Bigeye is the data observability platform that helps teams measure, improve, and communicate data quality clearly at any scale. Every time a data quality issue causes an outage, the business loses trust in the data. Bigeye helps rebuild trust, starting with monitoring. Find missing and busted reporting data before executives see it in a dashboard. Get warned about issues in training data before models get retrained on it. Fix that uncomfortable feeling that most of the data is mostly right, most of the time. Pipeline job statuses don't tell the whole story. The best way to ensure data is fit for use, is to monitor the actual data. Tracking dataset-level freshness ensures pipelines are running on schedule, even when ETL orchestrators go down. Find out about changes to event names, region codes, product types, and other categorical data. Detect drops or spikes in row counts, nulls, and blank values to ensure everything is populating as expected. -
7
Chaos Genius
Chaos Genius
Chaos Genius is a DataOps Observability platform for Snowflake. Enable Snowflake Observability to reduce Snowflake costs and optimize query performance.Starting Price: $500 per month -
8
IBM Databand
IBM
Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems. -
9
Acceldata
Acceldata
Acceldata is an Agentic Data Management company helping enterprises manage complex data systems with AI-powered automation. Its unified platform brings together data quality, governance, lineage, and infrastructure monitoring to deliver trusted, actionable insights across the business. Acceldata’s Agentic Data Management platform uses intelligent AI agents to detect, understand, and resolve data issues in real time. Designed for modern data environments, it replaces fragmented tools with a self-learning system that ensures data is accurate, governed, and ready for AI and analytics. -
10
Observo AI
Observo AI
Observo AI is an AI-native data pipeline platform designed to address the challenges of managing vast amounts of telemetry data in security and DevOps operations. By leveraging machine learning and agentic AI, Observo AI automates data optimization, enabling enterprises to process AI-generated data more efficiently, securely, and cost-effectively. It reduces data processing costs by over 50% and accelerates incident response times by more than 40%. Observo AI's features include intelligent data deduplication and compression, real-time anomaly detection, and dynamic data routing to appropriate storage or analysis tools. It also enriches data streams with contextual information to enhance threat detection accuracy while minimizing false positives. Observo AI offers a searchable cloud data lake for efficient data storage and retrieval. -
11
DataBahn
DataBahn
DataBahn.ai is redefining how enterprises manage the explosion of security and operational data in the AI era. Our AI-powered data pipeline and fabric platform helps organizations securely collect, enrich, orchestrate, and optimize enterprise data—including security, application, observability, and IoT/OT telemetry—for analytics, automation, and AI. With native support for over 400 integrations and built-in enrichment capabilities, DataBahn streamlines fragmented data workflows and reduces SIEM and infrastructure costs from day one. The platform requires no specialist training, enabling security and IT teams to extract insights in real time and adapt quickly to new demands. We've helped Fortune 500 and Global 2000 companies reduce data processing costs by over 50% and automate more than 80% of their data engineering workloads. -
12
Tenzir
Tenzir
Tenzir is a data pipeline engine specifically designed for security teams, facilitating the collection, transformation, enrichment, and routing of security data throughout its lifecycle. It enables users to seamlessly gather data from various sources, parse unstructured data into structured formats, and transform it as needed. It optimizes data volume, reduces costs, and supports mapping to standardized schemas like OCSF, ASIM, and ECS. Tenzir ensures compliance through data anonymization features and enriches data by adding context from threats, assets, and vulnerabilities. It supports real-time detection and stores data efficiently in Parquet format within object storage systems. Users can rapidly search and materialize necessary data and reactivate at-rest data back into motion. Tension is built for flexibility, allowing deployment as code and integration into existing workflows, ultimately aiming to reduce SIEM costs and provide full control. -
13
Cribl AppScope
Cribl
AppScope is a new approach to black-box instrumentation delivering ubiquitous, unified telemetry from any Linux executable by simply prepending scope to the command. Talk to any customer using Application Performance Management, and they’ll tell you how much they love their solution, but they wish they could extend it to more of their applications. Most have 10% or fewer of their apps instrumented for APM, and are supplementing what they can with basic metrics. Where does this leave the other 80%? Enter AppScope. No language-specific instrumentation. No application developers required. AppScope is language agnostic and completely userland; works with any application; scales from the CLI to production. Send AppScope data to any existing monitoring tool, time series database, or log tool. AppScope allows SREs and Ops teams to interrogate running applications to discover how they work and their behavior in any deployment context, from on-prem to cloud to containers.
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