Sold by: Sifflet
Sifflet is the leading end-to-end data observability platform built for data engineers and data consumers. The platform includes data quality monitoring, metadata management, and a data catalog with deep lineage capabilities.
4.3
Overview
Sifflet is a data observability platform designed to create order and visibility within the modern data stack. With Sifflet, organizations achieve a data program that is organized, accessible, and solvable.
Organized: Sifflet provides a unified and governed platform for seamless collaboration among teams, guaranteeing thorough and consistent monitoring of data pipelines and assets, as well as providing visibility across teams.
Sifflet offers deep integration capabilities within the modern data stack, centralized documentation and lineage, and a powerful metadata search engine.
Accessible: Sifflet ensures that every user effortlessly interacts with the product in the most user-friendly manner possible, with the product's programmatic capabilities for technical teams, or through the UI for non-technical teams.
Data is easy to access with a simple UI that offers automated and intuitive functionality.
The data catalog feature ensures data is findable and searchable.
For engineers, they will find it is easy to connect Sifflet with coding workflows.
Solvable: Sifflet helps teams swiftly resolve and detect data anomalies, achieving the shortest time-to-resolution through comprehensive root cause analysis, and business impact assessment.
Pricing: For questions about pricing and custom contract options, please contact Sifflet directly.
Highlights
- Deep integration capabilities within the modern data stack, centralized documentation and linerage, and a powerful metadata search engine.
- Data catalog and intuitive UI for data findability and access.
- Quality monitoring and alerting detects data anomalies fast with root cause analysis functionality.
Details
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/12 months |
|---|---|
Data Observability Platform Credits | $48,000.00 |
Dimensions summary
You buy access to the Sifflet data observability platform through a contract measured in Data Observability Platform Credits. This is a single usage-based dimension: you draw down credits as you use the platform rather than paying per named plan or instance size. Pricing scales with your consumption of credits, so larger monitoring needs draw more credits from your contract. Because there is one credit-based dimension, your cost tracks how much of the platform you use rather than a fixed set of feature tiers.
Top-of-mind questions for buyers
Credits are the billing unit you draw down as you use the platform. Consumption tracks your monitoring activity, such as the number of assets monitored and the monitors running against them. The marketplace listing does not break down a fixed per-credit rate for each action, so confirm specific credit consumption rates with the vendor.
Credit draw grows with the assets you monitor and the monitors you run. Adding more monitored tables, dashboards, or pipelines increases consumption. New monitors that match existing notification rules run automatically, which also affects usage. Cost tracks how much of the platform you use, so heavier monitoring draws more credits.
Credits cover the observability platform, including data catalog, freshness, schema, volume, and custom metric monitors, data lineage, incident management, and notification rules that route alerts to channels like email or ticketing tools. Anomaly detection and root-cause analysis are part of the platform you consume credits against.
www.siffletdata.com
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Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
Dedicated account manager and customer success engineer. Support is available through email, Slack, or Microsoft Teams. Contact us: https://www.siffletdata.com/contact Support email: support@siffletdata.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Data Quality Monitoring and Alerting
Detects data anomalies with root cause analysis functionality and alerting capabilities
Metadata Management and Search
Provides a powerful metadata search engine with centralized documentation and lineage tracking
Data Catalog
Offers data catalog with deep lineage capabilities for data findability and searchability
Modern Data Stack Integration
Supports deep integration capabilities within the modern data stack for seamless connectivity
Programmatic and User Interface Access
Provides both programmatic capabilities for technical teams and intuitive UI for non-technical users
Unified Search Across Data Stack
Search functionality that surfaces results across databases, data lakes, BI platforms, ML feature stores, and orchestration tools within a multi-cloud environment.
End-to-End Lineage Tracing
Lineage tracking capability that traces data journey across platforms, datasets, ETL/ELT pipelines, charts, and dashboards at table, column, and job levels.
AI-Powered Metadata Management
Metadata graph with AI-generated documentation, AI anomaly detection for freshness and volume metrics, and smart assertions for data quality monitoring.
Data Quality Monitoring and Observability
End-to-end observability with user-created data quality checks, freshness SLA monitoring, schema tracking, column quality assessment, and custom SQL evaluation through API.
Automated Governance and Compliance
Lineage-driven compliance classification, automated shift-left governance integration, continuous compliance monitoring with forms and impact analysis, and metadata harmonization across source systems.
Cross-Stack Environment Mapping
Connects to warehouse, orchestrator, and code to build a continuously updated understanding of the data environment across all components
Incident Resolution with Root Cause Analysis
Traces root cause across warehouse, orchestrator, and code infrastructure and automatically opens pull requests with validated fixes
Automated Pipeline Development and Maintenance
Operates across the full data engineering lifecycle including incident resolution, pipeline building, migration acceleration, and pipeline health maintenance
Rapid Environment Integration
Establishes cross-stack map within hours of connection without requiring MCPs, skill configuration, or data harness maintenance
Persistent Knowledge Accumulation
Stores every fix, validation, and explanation in the Living Map to enable institutional knowledge retention and accelerate resolution of subsequent incidents
Standard contract
No
Customer reviews
It was good and very useful tool
Reviewed on Jul 15, 2026
Review provided by G2
What do you like best about the product?
Dynamic conditions on pattern recognition
What do you dislike about the product?
nothing as much, as of now I'm good with it
What problems is the product solving and how is that benefiting you?
Monitoring our Raw data misses
Maritime
Proactive Data Quality Monitoring
Reviewed on Jun 17, 2026
Review provided by G2
What do you like best about the product?
Sifflet is most helpful for proactively monitoring data quality, detecting issues early, and linking them to business impact, which helps teams prioritize and act faster
What do you dislike about the product?
Main drawbacks iare some limitations in customization and alert management.
What problems is the product solving and how is that benefiting you?
Lack of trust in data → ensures data quality and reliability across pipelines
Reactive firefighting → shifts teams to proactive issue detection with anomaly monitoring
No visibility on data flows → provides lineage and full-stack visibility to understand impacts
Alert overload / low prioritization → links technical issues to real business impact to focus on what matters
Reactive firefighting → shifts teams to proactive issue detection with anomaly monitoring
No visibility on data flows → provides lineage and full-stack visibility to understand impacts
Alert overload / low prioritization → links technical issues to real business impact to focus on what matters
Maritime
Great Error Alerts, But Not User-Friendly for Data Analysts
Reviewed on Jun 17, 2026
Review provided by G2
What do you like best about the product?
I like that it detects errors and sends them directly by email every day.
What do you dislike about the product?
From my perspective as a data analyst, it isn’t user-friendly enough, especially compared with what my company announced.
What problems is the product solving and how is that benefiting you?
I have data quality errors in my work, and it gives me a list every day so I can address them directly on my side.
Luciana S.
Sifflet Delivers Fast, Seamless Data Observability with Clear Dashboards
Reviewed on May 15, 2026
Review provided by G2
What do you like best about the product?
Sifflet provides a robust data observability, mechanism, and this includes automated monitoring, of datasets, pipelines and others
The interface, more so the dashboard is completely understandable and there is no technical orientation needed
The procedure for anomalies detection is so fast and seamless, and this identifies any missing data and trends that are unlikely or unusual
Sifflet provides a significant insight on the root cause for any problem, where it uses BI tools and ensures proper troubleshooting
The integration with modern cloud apps is another robust feature and it connects with items such ad BigQuery and Looker
The sharing of any visibility and analytical reports is well done and this boosts collaboration
The interface, more so the dashboard is completely understandable and there is no technical orientation needed
The procedure for anomalies detection is so fast and seamless, and this identifies any missing data and trends that are unlikely or unusual
Sifflet provides a significant insight on the root cause for any problem, where it uses BI tools and ensures proper troubleshooting
The integration with modern cloud apps is another robust feature and it connects with items such ad BigQuery and Looker
The sharing of any visibility and analytical reports is well done and this boosts collaboration
What do you dislike about the product?
Small enterprises finds Sifflet an expensive solution that demands a hefty price or budget
Some false positives and too many alerts makes the application less efficient and appealing
Some false positives and too many alerts makes the application less efficient and appealing
What problems is the product solving and how is that benefiting you?
Sifflet is a helpful approach, that helps us in handling and identifying broken data pipelines, snd this makes business users more aware
The dashboard is very accurate and this brings accuracy in reporting for business proficiency
The app creates a robust trust in BI data and business analytics, and this increases the operational performance of a firm
The app is versatile in helping us identify any root cause for data inefficiencies and quality problems
Sifflet controls chances of data downtime, and this involves handling failed transformations
The app has impressive governance and this involves dependency in integrating with modern databases
The dashboard is very accurate and this brings accuracy in reporting for business proficiency
The app creates a robust trust in BI data and business analytics, and this increases the operational performance of a firm
The app is versatile in helping us identify any root cause for data inefficiencies and quality problems
Sifflet controls chances of data downtime, and this involves handling failed transformations
The app has impressive governance and this involves dependency in integrating with modern databases
Jouri Q.
Flexible, Unified Platform for Data Reliability and Observability
Reviewed on May 14, 2026
Review provided by G2
What do you like best about the product?
I like that it provides a unified platform for data reliability and for observing data flows. From an implementation perspective, I really appreciate the platform’s flexibility: it lets me adapt it to each organization’s specific architecture and operational requirements, instead of forcing rigid patterns.
What do you dislike about the product?
They adapt well to the needs of different teams, take a genuinely collaborative approach, provide 24/7 support, and cover the essential aspects of observability. Overall, I don’t have anything negative to say about them.
What problems is the product solving and how is that benefiting you?
We use it regularly to monitor, prioritize, and better understand data-related issues. It helps reduce tool sprawl and allows teams to manage data health effectively at an enterprise scale, which has noticeably simplified our day-to-day work.