Databand
Databand is a Tel Aviv-based data observability platform, founded in 2018, that uses machine learning-powered anomaly detection to monitor data and ML pipelines for enterprise data teams. It serves organizations requiring reliable data infrastructure for analytics and AI workloads via direct enterprise sales.
- Company typePrivate
- Founded2018
- HeadquartersNew York, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What Databand does
Databand is a private software company founded in 2018 and headquartered in Tel Aviv, Israel, that provides an observability platform for data and machine learning pipelines. The platform continuously monitors data flows, detects anomalies and pipeline failures, and alerts stakeholders via channels such as Slack, PagerDuty, and email. Its core technology stack centers on machine learning-powered anomaly detection applied to data quality and pipeline metadata, combined with real-time monitoring and pipeline-level observability. The product is differentiated from threshold-based legacy monitoring by using ML to identify data incidents proactively before they propagate to downstream analytics and AI workloads.
Databand serves enterprise data teams responsible for AI-driven decision-making and analytics reliability, addressing pain points around pipeline complexity, data quality issues, and delayed incident detection. The company operates a horizontal segmentation approach via direct enterprise sales, targeting organizations with large-scale data integration requirements. Pricing is not publicly disclosed, consistent with enterprise contract structures. The platform is positioned in buyer guides alongside competing data observability solutions including Monte Carlo, Bigeye, Acceldata, Datafold, and Soda, within a global data observability market projected to grow from $1.7 billion in 2025 to $9.7 billion by 2034 at a 21.3% CAGR.
The company has raised approximately $14.5 million across seed and Series A funding (Series A led by Accel in December 2020, with participation from Bessemer Venture Partners, Blumberg Capital, Differential Ventures, F2 Venture Capital, Lerer Hippeau, and Ubiquity Ventures). It maintains a lean team of 11-50 employees with co-founders Joshua Benamram (CEO), Evgeny Shulman (CTO), and Victor Shafran (CPO) continuing in their roles since inception. No subsequent funding rounds, acquisitions, or material strategic events have been documented in available sources.
Databand firmographics
Firmographics- Name
- Databand
- Website
- https://databand.ai
- Company type
- Private
- Founded year
- 2018
- Headcount range
- 11–50 employees
- Short description
- Databand is a Tel Aviv-based data observability platform, founded in 2018, that uses machine learning-powered anomaly detection to monitor data and ML pipelines for enterprise data teams. It serves organizations requiring reliable data infrastructure for analytics and AI workloads via direct enterprise sales.
- Ownership category
- akta.pro rank
Databand industry classification
Industry- Product category
- Data Observability Software
- NAICS
- Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518)
- SIC
- Services-Computer Programming, Data Processing, Etc. (7370)
- akta.pro primary industry
- Data Observability & Monitoring (HDAEADAI)
- akta.pro secondary industry
- Pipeline Orchestration & Workflow Automation (HDAAABAD)
Keywords
Where Databand is headquartered
LocationHeadquarters
- HQ city
- New York
- HQ country
- United States
- HQ region
- North America
Markets served
Databand business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Operations
Distribution channels1 record
Marketing channels2 records
Databand product offering
Product offeringCore offering
Databand provides an observability platform for data and machine learning pipelines. The platform uses machine learning-powered anomaly detection, real-time monitoring, and comprehensive pipeline observability to proactively identify data quality issues and pipeline failures before they impact downstream analytics and AI workloads.
Differentiator
Problem solved
Functional benefit
Products and services
- Databand Data Observability Platform An observability platform for data and machine learning pipelines that uses machine learning-powered anomaly detection, real-time monitoring, and pipeline observability to proactively identify data quality issues and pipeline failures. Targeted at enterprise data teams running AI and analytics workloads that require trustworthy, reliable data.
Companies that use Databand
Customer profileSegments1 record
Ideal customer profiles1 record
Databand technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
Feature3 records
Databand partnerships and signals
Strategic signalScale indicators2 records
Recent moves4 records
Expansion highlights3 records
Databand competitors and assessment
Company assessmentBroad incumbents
- Databricks: Databricks provides the Lakehouse Platform with Unity Catalog and native data quality/lineage features that overlap with Databand's observability use cases for enterprise data and ML pipelines.
- Snowflake: Snowflake's data cloud includes native data observability and monitoring features (e.g., Snowflake Observability) that compete with Databand for enterprise data pipeline reliability budgets.
- IBM (watsonx.data integration): IBM's watsonx.data integration suite includes native data observability capabilities for monitoring pipelines, detecting anomalies, and managing data incidents — competing with Databand as part of a broader data and AI platform portfolio.
Direct peers
- Soda: Soda offers data observability and data quality testing tools for data engineers, including anomaly detection and pipeline monitoring — named alongside Databand as a top data observability vendor in 2025.
- Datafold: Datafold provides data observability and data diff/regression testing for analytics pipelines, targeting data engineering teams with similar use cases to Databand's data quality and pipeline monitoring offering.
- Monte Carlo Data: Monte Carlo is a leading data observability platform offering data monitoring, anomaly detection, and lineage for enterprise data teams — directly competing with Databand in the same product category and buyer profile.
- Bigeye: Bigeye provides a data observability platform with anomaly detection, data quality monitoring, and freshness checks for data pipelines — a direct competitor named alongside Databand in 2025 buyer guides.
- Acceldata: Acceldata offers a unified data observability platform for data pipelines, including data reliability, pipeline monitoring, and performance analytics — a direct competitor co-listed with Databand in 2025 observability buyer guides.
Emerging players
- WhyLabs: WhyLabs provides an AI observability platform for data and ML pipelines with anomaly detection and monitoring, overlapping with Databand's ML pipeline observability positioning.
- Great Expectations: Great Expectations is an open-source data quality framework with commercial offerings for data validation and testing — an emerging player in adjacent data reliability tooling that overlaps with Databand's pipeline monitoring use case.
Market position
Strengths4 records
Weaknesses4 records
Competitive moat3 records
Key risks5 records
Key highlights6 records
Customer concentration
Databand social profiles
Digital presenceDataband financial estimates
Financial estimateRevenue estimate
Valuation estimate
Databand leadership team
Management profileNumber of profiles
Profiles3 records
Databand funding detail
Funding detailFunding overview
Funding rounds3 records
Investors9 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Databand M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Databand
What does Databand do?
Databand provides an observability platform for data and machine learning pipelines. The platform uses machine learning-powered anomaly detection, real-time monitoring, and comprehensive pipeline observability to proactively identify data quality issues and pipeline failures before they impact downstream analytics and AI workloads.
When was Databand founded?
Databand was founded in 2018. It employs 11 to 50 people.
Where is Databand based?
Databand is headquartered in New York, United States, in the North America region.
Who are Databand's main competitors?
Broad incumbents on record are Databricks, Snowflake and IBM (watsonx.data integration). Direct peers are Soda, Datafold, Monte Carlo Data, Bigeye and Acceldata. Emerging players are WhyLabs and Great Expectations.
Does Databand have an API?
No public API is recorded for Databand.
What industry is Databand in?
Databand's product category is Data Observability Software. Its primary akta.pro industry code is HDAEADAI, Data Observability & Monitoring, with a secondary code of HDAAABAD, Pipeline Orchestration & Workflow Automation. Its NAICS code is 518 and its SIC code is 7370.