Home
Pricing
%%Flexible pricing for %%every stage of data maturity
Build data trust at your own pace, from first monitors to enterprise-wide observability.
Got Snowflake credits sitting around? You can use them here.
Let’s chat about how it works.
Entry
Growth
Enterprise
Number of Assets Monitored
Up to 500
Up to 1,000
1,000+ (scales flexibly)
Great for...
Small but mighty data teams
Cross-functional data teams
Large, regulated or complex organizations
Procurement Process
Self-Serve/Marketplaces
Sales-Assisted/Marketplaces
Direct Enterprise Sales or Channel
What you'll get
Core Data Observability & Catalog
(Fundamental metrics: freshness, schema, volume, custom metrics...)
Business-Aware Lineage & Impact Analysis
Automated Root-Cause Analysis
AI-Powered Incident Management
Advanced Governance
(RBAC, Audit logs...)
Data Observability Agent
SSO
Snowflake/BigQuery/S3 Data Sharing
Early Access to Upcoming Data Observability Agents
Pipeline Monitoring
Deployment
Deployment Type
SaaS
SaaS
SaaS/Hybrid/Self-hosted
SLA & Support
Standard
Priority
Enterprise (24/7, white-glove)
Onboarding & Success Program
Guided
Dedicated
Enterprise (including executive sponsorship)
What Our Customers Say
See Sifflet in action!
Curious about how Sifflet can transform the way your team works with data?
Join our 30-min biweekly demo to see how data leaders, engineers, and platform teams use Sifflet to detect, resolve, and prevent issues—before they impact the business.
Looking for more?
Customer Story
Automating Data Quality at Scale: Inside Penguin Random House’s Sifflet Implementation
Blogpost
Data Observability, Five Years In: Why the Old Playbook Doesn’t Work Anymore
Checklist
Access this (really) free checklist that helps you pick a data observability platform that pays off in speed, trust & measurable impact.
Let's make it a thing
One form, one message, one step closer to data you can actually trust.
Get in touch
Still have a question in mind ?
Contact Us
Frequently asked questions
Why is data observability becoming such a priority for enterprises in 2025?
Great question! As more organizations rely on AI and analytics for decision-making, ensuring data quality, health, and reliability has become non-negotiable. Data observability platforms like Sifflet help teams detect issues early, reduce downtime, and maintain trust in their data pipelines.
Can Sifflet monitor data quality in real-time?
Absolutely! Sifflet supports real-time metrics and data quality monitoring across your pipelines. Our AI agents continuously track data freshness, schema changes, and anomalies, so you’re alerted the moment something looks off. It’s like having a 24/7 data guardian that ensures your business decisions are based on accurate and timely information.
How can I track the success of my data team?
Define clear success KPIs that support ROI, such as improvements in SLA compliance, reduction in ingestion latency, or increased data reliability. Using data observability dashboards and pipeline health metrics can help you monitor progress and communicate value to stakeholders. It's also important to set expectations early and maintain strong internal communication.
What role does Sifflet play in Etam’s data governance efforts?
Sifflet supports Etam by embedding data governance into their workflows through automated monitoring, anomaly detection, and data lineage tracking. This gives the team better visibility into their data pipelines and helps them troubleshoot issues quickly without slowing down innovation.
What are the key features to look for in a data observability platform?
When evaluating an observability platform, look for strong data lineage tracking, real-time metrics collection, anomaly detection capabilities, and broad integrations across your data stack. Features like field-level lineage, ease of setup, and user-friendly dashboards can make a big difference too. At Sifflet, we believe observability should empower both technical and business users with the context they need to trust and act on data.
Can Sifflet help me monitor data drift and anomalies beyond what dbt offers?
Absolutely! While dbt is fantastic for defining tests, Sifflet takes it further with advanced data drift detection and anomaly detection. Our platform uses intelligent monitoring templates that adapt to your data’s behavior, so you can spot unexpected changes like missing rows or unusual values without setting manual thresholds.
What kind of integrations does Sifflet offer for data pipeline monitoring?
Sifflet integrates with cloud data warehouses like Snowflake, Redshift, and BigQuery, as well as tools like dbt, Airflow, Kafka, and Tableau. These integrations support comprehensive data pipeline monitoring and ensure observability tools are embedded across your entire stack.
Why should organizations shift from firefighting to fire prevention in their data operations?
Shifting to fire prevention means proactively addressing data health issues before they impact users. By leveraging data lineage and observability tools, teams can perform impact assessments, monitor data quality, and implement preventive strategies that reduce downtime and improve SLA compliance.
PRODUCT
Subscribe to our blog
The latest in data observability sent to your inbox.