Best Observability Tools for Amazon Redshift
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Compare the Top Observability Tools that integrate with Amazon Redshift as of October 2025
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This a list of Observability tools that integrate with Amazon Redshift. Use the filters on the left to add additional filters for products that have integrations with Amazon Redshift. View the products that work with Amazon Redshift in the table below.
What are Observability Tools for Amazon Redshift?
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 Amazon Redshift currently available using the table below. This list is updated regularly.
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1
New Relic
New Relic
New Relic empowers enterprises with intelligent observability solutions, providing unmatched visibility across your tech stack. Our AI-driven, unified data platform centralizes telemetry from front-end to infrastructure, enabling real-time insights and proactive issue resolution. With advanced tools like automated alerts, customizable dashboards, and full-stack analysis, New Relic helps you optimize performance, reduce downtime, and deliver superior digital experiences. Simplifying enterprise-scale observability, New Relic turns your system data into a strategic asset, driving operational efficiency and innovation. Start your observability transformation today.Starting Price: Free -
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. -
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SolarWinds AppOptics
SolarWinds
SolarWinds® AppOptics™ is a simple, powerful, and affordable SaaS-based infrastructure & application monitoring tool for custom on-premises, cloud, and hybrid systems. By enabling quick identification of performance problems across the stack from the application, to underlying infrastructure, down to the line of code, AppOptics helps reduce MTTR. AppOptics was thoughtfully designed for simple setup and use by all IT professionals with powerful features to quickly and automatically pinpoint performance issues removing the guesswork from troubleshooting. AppOptics enables you to align infrastructure and application performance objectives side by side with business objectives.Starting Price: $9.99/host/month* -
4
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 -
5
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. -
6
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. -
7
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. -
8
Last9
Last9
Visualize your microservices end-to-end, from your CDN all the way to your databases, including external dependencies. Automatically measure baselines and get recommendations of SLIs and SLOs. Understand and measure the impact across microservices. Every change introduces a ripple through your connected system. Did a security group change affect Login API? Last9 makes it easy to locate the ‘last change’ that triggered an incident. Last9 is a modern reliability stack. It’s designed to leverage your existing observability tricks and allow you to build and enforce mental models on top of your data to help you cover infrastructure, service, and product metrics with minimal effort and distractions. With all the love and passion for reliability, we address the challenges of every layer to make running systems at scale fun and embarrassingly easy! Last9 leverages the knowledge graph to automatically generate a map view of known infrastructure and service components. -
9
The only real-time, analytics-driven multicloud monitoring solution for all environments (formerly SignalFx). Monitor any environment on a massively scalable streaming architecture. Open, flexible data collection and rapid visualizations of services in seconds. Purpose built for ephemeral and dynamic cloud-native environments at any scale (e.g., Kubernetes, container, serverless). Detect, visualize and resolve issues as soon as they arise. Monitor infrastructure performance in real-time at cloud scale through predictive streaming analytics. Over 200 pre-built integrations for cloud services and out-of-the-box dashboards for rapid visualization of your entire stack. Autodiscover, breakdown, group, and explore clouds, services and systems. Quickly and easily understand how your infrastructure behaves across different services, availability zones, Kubernetes clusters and more.
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10
StackState
StackState
StackState's Topology and Relationship-Based Observability platform lets you manage your dynamic IT environment more effectively by unifying performance data from your existing monitoring tools into a single topology. Enabling you to: 1. 80% Decreased MTTR: by identifying the root cause and alerting the right teams with the correct information. 2. 65% Fewer Outages: through real-time unified observability and more planful planning. 3. 3x Faster Releases: by giving time back to developers to increase implementations. Get started today with our free guided demo: https://www.stackstate.com/schedule-a-demo
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