Elementary

Elementary

Elementary Data
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About

Elementary is a data observability and reliability platform for analytics and data engineering teams. It monitors data pipelines and warehouse assets, detects freshness, volume, schema and quality anomalies, and brings dbt and custom test results into a shared view. Teams can investigate incidents, trace impact through column-level lineage, review data health and performance, and manage asset descriptions, ownership and governance. Elementary Cloud adds dashboards, alert routing, collaboration, a catalog and AI-assisted workflows. An open-source self-hosted option supports code-first monitoring in the customer's environment. The platform connects warehouse, transformation, BI, orchestration, code and messaging tools. Its MCP server connects AI tools with Elementary data context. It serves data, analytics and platform teams, as well as business users who need to find, validate, monitor and understand data.

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 and analytics engineering teams, data platform teams, and business users responsible for data quality, reliability, governance, and discovery.

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 Supported

Support

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

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

No images available

Screenshots and Videos

Pricing

Elementary Cloud pricing is based on seats and environments. Scale includes up to 10 editor seats and 1,000 tables; Enterprise includes up to 20 editor seats, 40 viewer seats, and 3,000 tables; Unlimited includes unlimited seats and 3,000 tables. Additional monitored-table capacity and AI Layer credits incur extra charges.
Free Version Supported
Free Trial 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

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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 Supported
Webinars Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Not Supported

Company Information

Elementary Data
Founded: 2021
Israel
www.elementary-data.com

Company Information

Sifflet
United States
www.siffletdata.com

Alternatives

Alternatives

dbt

dbt

dbt Labs

Categories

Categories

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

Integrations

Amazon Redshift Supported
Apache Airflow Supported
Google Cloud BigQuery Supported
Looker Supported
Microsoft Teams Supported
PagerDuty Supported
Slack Supported
Snowflake Supported
Tableau Supported
dbt Supported
Amazon Athena Not Supported
Amazon S3 Not Supported
Apache Hive Not Supported
Census Not Supported
Databricks Supported
GitHub Supported
Microsoft Azure Not Supported
PostgreSQL Not Supported
SQL Server Not Supported
Stitch Not Supported

Integrations

Amazon Redshift Supported
Apache Airflow Supported
Google Cloud BigQuery Supported
Looker Supported
Microsoft Teams Supported
PagerDuty Supported
Slack Supported
Snowflake Supported
Tableau Supported
dbt Supported
Amazon Athena Supported
Amazon S3 Supported
Apache Hive Supported
Census Supported
Databricks Not Supported
GitHub Not Supported
Microsoft Azure Supported
PostgreSQL Supported
SQL Server Supported
Stitch Supported
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