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About

DataKitchen is a DataOps software platform that helps organizations automate data quality testing, monitor data pipelines, and manage analytics workflows. Its product suite includes DataOps Data Quality TestGen, DataOps Process Observability, and DataOps Automation. TestGen automatically profiles databases, generates data quality tests, identifies anomalies, and monitors data reliability across existing data environments. DataOps Process Observability provides end-to-end visibility into data pipelines, datasets, and workflows to detect failures, delays, and performance bottlenecks. DataOps Automation enables teams to orchestrate data pipelines, manage development environments, automate deployments, and integrate testing into production workflows. The platform supports integrations with Snowflake, Databricks, BigQuery, Airflow, dbt, and other data technologies, with open-source and enterprise deployment options.

About

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.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Data engineers, analytics engineers, data scientists, data architects, DataOps teams, database administrators, business intelligence professionals, IT operations teams, and enterprises seeking automated data quality testing, pipeline observability, data workflow orchestration, and reliable analytics infrastructure

Audience

Teams and companies requiring a solution to monitor their data assets, metadata, and infrastructure

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 4.5 / 5
design 5.0 / 5
support 4.0 / 5

Pros & Cons from Real Users

Pros

  • AI-based anomaly detection works flawlessly Easy data lineage visualization Customizable metrics for business-specific monitoring Smooth cloud integration
  • To call out some of the top features, they would be:- ✅ The ability to connect to multiple data sources; giving you great observability of data no matter what platform you use. ✅ The UI is clean, simple and easy to use. Setting up a new data source is easy, even uploading dbt manifest files via their API is a simple few commands. ✅ Their documentation on getting things set up and working is very easy to read; it’s not bloated and tells you exactly what you need to do. ✅Their communication with us has been a great experience. They’ve fixed bugs we’ve raised to them, informed us of new updates, and overall been very receptive of feedback.

Cons

  • Mobile interface could be slightly improved Initial setup requires some familiarization for complex pipelines
  • Sifflet are still developing some features, polishing existing ones and ironing out minor bugs (more like quality of life features). So there’s nothing major that would be a deal breaker. If I had to call out some points that need development they would be:- 🤔 Their ‘Domain’ feature (ability to put data assets into domains, then limit users to a domain) is still in it’s basic form. It works, but needs some tweaks before it can be a real sellable feature. 🤔Exploring the lineage of a very large lineage graph can be difficult due to the number of relationships/dependencies a model may have. This may be more of an issue with your own DAG architecture than Sifflet, but it’s worth keeping in mind if your models are inherently complex and coupled to one another. Thankfully, Sifflet are working on a new UI for their lineage graph and have demo'd it with us, so this should be a lot smoother in the near future.

Training

Documentation Not Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Not Supported

Company Information

DataKitchen
Founded: 2013
United States
datakitchen.io

Company Information

Sifflet
United States
www.siffletdata.com

Alternatives

Alternatives

dbt

dbt

dbt Labs

Categories

Automated Testing Supported
Data Observability Supported
Data Pipeline Supported
Data Quality Supported
DataOps Supported

Categories

Data Catalog Supported
Data Engineering Supported
Data Lineage Supported
Data Observability Supported
Data Quality Supported
DataOps Supported
Observability Supported

Integrations

Google Cloud BigQuery Supported
PostgreSQL Supported
SQL Server Supported
Slack Supported
Snowflake Supported
Airbyte Not Supported
Amazon EMR Not Supported
Amazon QuickSight Not Supported
Census Not Supported
Datadog Not Supported
Firebolt Not Supported
Git Supported
Google Cloud Platform Not Supported
Hightouch Not Supported
Jira Supported
Kubernetes Supported
Looker Not Supported
Microsoft Power BI Not Supported
Microsoft Teams Not Supported
Opsgenie Not Supported

Integrations

Google Cloud BigQuery Supported
PostgreSQL Supported
SQL Server Supported
Slack Supported
Snowflake Supported
Airbyte Supported
Amazon EMR Supported
Amazon QuickSight Supported
Census Supported
Datadog Supported
Firebolt Supported
Git Not Supported
Google Cloud Platform Supported
Hightouch Supported
Jira Not Supported
Kubernetes Not Supported
Looker Supported
Microsoft Power BI Supported
Microsoft Teams Supported
Opsgenie Supported
Claim DataKitchen DataOps Automation and update features and information
Claim DataKitchen DataOps Automation and update features and information
Claim Sifflet and update features and information
Claim Sifflet and update features and information