Product

Data Security

%%Simply%% Secure

Sifflet makes no compromises when it comes to ensuring your security, risk mitigation, and compliance.

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Least Privilege Policies

Sifflet helps you manage who can access what data. It features RBAC principles to grant or restrict access based on a user’s role in the organization, rather than managing individual permissions.

A No Data Storage Approach

Our approach eliminates persistent data storage, with transient data handling and ephemeral computing principles.

State of the Art Isolation

Sifflet uses single tenancy architecture, so each and every client benefits from a dedicated and isolated instance of our tooling, infrastructure, and associated resources.

ENSURE

Product Security

Sifflet gives you peace of mind with tools to keep access to your environment protected.

SaaS or self-hosted deployment
Cross-IdP SSO support
RBAC

ISOLATE

Platform Security

Security at the platform level to keep each and every client safe.

Single tenancy architecture for state of the art isolation
No data alteration and least privilege policy
No data storage approach

PROTECT

Compliance Certifications

Your data’s sensitive. Sifflet is certified compliant across a range of standards.

SOC 2
ISO 27001
GDPR
HIPAA

Reinforced %%Reliability%%

Sifflet’s monitoring features reinforce data reliability for all users, so business can deliver.

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Data Users

Enhance customer trust with tools that secure data and help your business align with regulatory and compliance requirements.

Data Engineers

Keep specific data pipelines and storage systems confidential and protect critical data assets from manipulation.

Data Leaders

Avoid legal issues, financial penalties and reputational damage associated with data mishandling, or unauthorized data access and breaches.

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sifflet a guide to assessing your need for a data observability

Insights

A Guide to Assessing your Need for Data Observability

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How Sifflet keeps your data safe

Product

Data quality for all - Un-siloed data quality

Need %%strong%% data protection?

Benefit from peace of mind that your sensitive data is safe and your business mitigates risk by remaining compliant.

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Sifflet’s AI Helps Us Focus on What Moves the Business

What impressed us most about Sifflet’s AI-native approach is how seamlessly it adapts to our data landscape — without needing constant tuning. The system learns patterns across our workflows and flags what matters, not just what’s noisy. It’s made our team faster and more focused, especially as we scale analytics across the business.

Simoh-Mohamed Labdoui

Head of Data

"Enabler of Cross Platform Data Storytelling"

"Sifflet has been a game-changer for our organization, providing full visibility of data lineage across multiple repositories and platforms. The ability to connect to various data sources ensures observability regardless of the platform, and the clean, intuitive UI makes setup effortless, even when uploading dbt manifest files via the API. Their documentation is concise and easy to follow, and their team's communication has been outstanding—quickly addressing issues, keeping us informed, and incorporating feedback. "

Callum O'Connor

Senior Analytics Engineer, The Adaptavist

"Building Harmony Between Data and Business With Sifflet"

"Sifflet serves as our key enabler in fostering a harmonious relationship with business teams. By proactively identifying and addressing potential issues before they escalate, we can shift the focus of our interactions from troubleshooting to driving meaningful value. This approach not only enhances collaboration but also ensures that our efforts are aligned with creating impactful outcomes for the organization."

Sophie Gallay

Data & Analytics Director, Etam

" Sifflet empowers our teams through Centralized Data Visibility"

"Having the visibility of our DBT transformations combined with full end-to-end data lineage in one central place in Sifflet is so powerful for giving our data teams confidence in our data, helping to diagnose data quality issues and unlocking an effective data mesh for us at BBC Studios"

Ross Gaskell

Software engineering manager, BBC Studios

"Sifflet allows us to find and trust our data"

"Sifflet has transformed our data observability management at Carrefour Links. Thanks to Sifflet's proactive monitoring, we can identify and resolve potential issues before they impact our operations. Additionally, the simplified access to data enables our teams to collaborate more effectively."

Mehdi Labassi

CTO, Carrefour Links

"A core component of our data strategy and transformation"

"Using Sifflet has helped us move much more quickly because we no longer experience the pain of constantly going back and fixing issues two, three, or four times."

Sami Rahman

Director of Data, Hypebeast

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Frequently asked questions

How does the shift from ETL to ELT impact data pipeline monitoring?

The move from ETL to ELT allows organizations to load raw data into the warehouse first and transform it later, making pipeline management more flexible and cost-effective. However, it also increases the need for data pipeline monitoring to ensure that transformations happen correctly and on time. Observability tools help track ingestion latency, transformation success, and data drift detection to keep your pipelines healthy.

How does data observability differ from traditional data quality monitoring?

Great question! Traditional data quality monitoring focuses on pre-defined rules and tests, but it often falls short when unexpected issues arise. Data observability, on the other hand, provides end-to-end visibility using telemetry instrumentation like metrics, metadata, and lineage. This makes it possible to detect anomalies in real time and troubleshoot issues faster, even in complex data environments.

Why is combining dbt Core with a data observability platform like Sifflet a smart move?

Combining dbt Core with a data observability platform like Sifflet helps data teams go beyond transformation and into full-stack monitoring. It enables better root cause analysis, reduces time to resolution, and ensures your data products are trustworthy and resilient.

Why should I care about metadata management in my organization?

Great question! Metadata management helps you understand what data you have, where it comes from, and how it’s being used. It’s a critical part of data governance and plays a huge role in improving data discovery, trust, and overall data reliability. With the right metadata strategy, your team can find the right data faster and make better decisions.

Is Sifflet planning to offer native support for Airbyte in the future?

Yes, we're excited to share that a native Airbyte connector is in the works! This will make it even easier to integrate and monitor Airbyte pipelines within our observability platform. Stay tuned as we continue to enhance our capabilities around data lineage, automated root cause analysis, and pipeline resilience.

Why is table-level lineage important for data quality monitoring and governance?

Table-level lineage helps you understand how data flows through your systems, which is essential for data quality monitoring and data governance. It supports impact analysis, pipeline debugging, and compliance by showing how changes in upstream tables affect downstream assets.

What’s the difference between a data catalog and a storage platform in observability?

A great distinction! Storage platforms hold your actual data, while a data catalog helps you understand what that data means. Sifflet connects both, so when we detect an anomaly, the catalog tells you what business process is affected and who should be notified. It’s how we turn raw telemetry into actionable insights for better incident response automation and SLA compliance.

What role does reverse ETL play in operational analytics?

Reverse ETL bridges the gap between data teams and business users by moving data from the warehouse into tools like CRMs and marketing platforms. This enables operational analytics, where business teams can act on real-time data. To ensure this process runs smoothly, data observability dashboards can monitor for pipeline errors and enforce data validation rules.

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