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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.

About

arcodash is a hosted business-intelligence and data-observability application for teams that need shared SQL reporting and checks on the data behind their dashboards. Users connect supported databases, warehouses, and other sources, explore data with a SQL editor or plain-language query assistance, and build charts, tables, metrics, and dashboards. Scheduled refreshes keep reports current. Data monitors can test conditions such as freshness, row counts, null rates, duplicates, and query thresholds, then send notifications through configured channels including email, Slack, and incident or team-messaging tools. AI features can help draft SQL, suggest visualizations and checks, and explain alerts using an organization's configured model provider. The cloud service is designed for data and analytics teams that create reports and monitor the underlying data quality.

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

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

Audience

Data and analytics teams of 10 to 300 people who write SQL and own the company's dashboards.

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 Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

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

Pricing

$59/month
Team costs $59/month or $600/year and includes unlimited seats, one data source, 1,500 monthly query runs, 25 monitors, and refreshes and checks as often as daily. Org costs $300/month or $3,000/year and includes unlimited seats, unlimited data sources, query runs, and monitors, with any schedule. Both plans include a 14-day free trial with no credit card.
Free Version Not Supported
Free Trial Supported

Reviews/Ratings

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

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:

Review this Software

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 Supported
In Person Not Supported

Training

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

Company Information

Sifflet
United States
www.siffletdata.com

Company Information

arcodash
Founded: 2026
Israel
www.arcodash.com

Alternatives

Alternatives

dbt

dbt

dbt Labs

Categories

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

Categories

Dashboard Supported
Data Observability Supported

Integrations

Amazon Athena Supported
Amazon Redshift Supported
Datadog Supported
Google Cloud BigQuery Supported
Microsoft Teams Supported
MySQL Supported
PagerDuty Supported
PostgreSQL Supported
SQL Server Supported
Slack Supported
Snowflake Supported
Amazon EMR Supported
Amazon QuickSight Supported
Apache Spark Supported
Elasticsearch Not Supported
Microsoft Azure Supported
MongoDB Not Supported
Prefect Supported
SQLite Not Supported
TiDB Not Supported

Integrations

Amazon Athena Supported
Amazon Redshift Supported
Datadog Supported
Google Cloud BigQuery Supported
Microsoft Teams Supported
MySQL Supported
PagerDuty Supported
PostgreSQL Supported
SQL Server Supported
Slack Supported
Snowflake Supported
Amazon EMR Not Supported
Amazon QuickSight Not Supported
Apache Spark Not Supported
Elasticsearch Supported
Microsoft Azure Not Supported
MongoDB Supported
Prefect Not Supported
SQLite Supported
TiDB Supported
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