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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
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Checklist
Access this (really) free checklist that helps you pick a data observability platform that pays off in speed, trust & measurable impact.
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One form, one message, one step closer to data you can actually trust.
Get in touch
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Frequently asked questions
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 are data teams moving away from Monte Carlo to newer observability tools?
Many teams are looking for more flexible and cost-efficient observability tools that offer better business user access and faster implementation. Monte Carlo, while a pioneer, has become known for its high costs, limited customization, and lack of business context in alerts. Newer platforms like Sifflet and Metaplane focus on real-time metrics, cross-functional collaboration, and easier setup, making them more appealing for modern data teams.
What is Flow Stopper and how does it help with data pipeline monitoring?
Flow Stopper is a powerful feature in Sifflet's observability platform that allows you to pause vulnerable pipelines at the orchestration layer before issues reach production. It helps with proactive data pipeline monitoring by catching anomalies early and preventing downstream damage to your data systems.
How does Sifflet ensure data security within its data observability platform?
At Sifflet, data security is built into the foundation of our data observability platform. We follow three core principles: least privilege, no storage, and single tenancy. This means we only use read-only access, never store your data, and isolate each customer’s environment to prevent cross-tenant access.
How can data observability support a strong data governance strategy?
Data observability complements data governance by continuously monitoring data pipelines for issues like data drift, freshness problems, or anomalies. With an observability platform like Sifflet, teams can proactively detect and resolve data quality issues, enforce data validation rules, and gain visibility into pipeline health. This real-time insight helps governance policies work in practice, not just on paper.
How does Sifflet help optimize Data as a Product initiatives?
Sifflet enhances DaaP initiatives by providing comprehensive data observability dashboards, real-time metrics, and anomaly detection. It streamlines data pipeline monitoring and supports proactive data quality checks, helping teams ensure their data products are accurate, well-governed, and ready for use or monetization.
How does Sifflet make it easier to manage data volume at scale?
Sifflet simplifies data volume monitoring with plug-and-play integrations, AI-powered baselining, and unified observability dashboards. It automatically detects anomalies, connects them to business impact, and provides real-time alerts. Whether you're using Snowflake, BigQuery, or Kafka, Sifflet helps you stay ahead of data reliability issues with proactive monitoring and alerting.
What benefits did jobvalley experience from using Sifflet’s data observability platform?
By using Sifflet’s data observability platform, jobvalley improved data reliability, streamlined data discovery, and enhanced collaboration across teams. These improvements supported better decision-making and helped the company maintain a strong competitive edge in the HR tech space.
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