Telmai Named a Leader in GigaOm 2023 Radar Report for Data Observability

Telmai, the open architecture, AI-driven data observability company, today announced that it has been named a Leader in the 2023 GigaOm Radar Report for Data Observability. This report is the first-ever Data Observability market research with a complete assessment of competing technologies framed in well-defined features and criteria. 

GigaOM, the leading technology-focused analyst and research firm, recognizes Telmai as a Leader in Data Observability, noting that, “The platform’s low-code functionality, considerable automation, and data pipeline support will go a long way with users, as will its attribute-level anomaly detection and support for open architecture.”

According to the report, “Telmai automatically scans source data, extracts relevant metrics, and organizes them into automatic data quality KPIs. The platform’s data observability applies to structured, semi-structured, and streaming data, message queues, data warehouses, cloud storage, data lakes, and APIs.”

Among the 15 Data Observability solutions evaluated by GigaOm, Telmai received “Exceptional” scores for serving both the Enterprise and SMB market segments and the Data Engineers and Business User segments. 

Included in GigaOm’s “Key Criteria for Evaluating Data Observability Solutions” section of the report, Telmai received the highest possible scores for advanced data quality, schema change monitoring, AIOps, edge capabilities, and BI-like experience, with the report noting that, “The platform includes, yet goes beyond, assessing data reliability according to metadata to provide column-level patterns and outliers about specific data values.”

In the report, Telmai also falls in the Innovation/Platform Play quadrant as a Forward Mover. The Innovation axis highlights technical innovation and a more aggressive approach, while the Platform axis displays a broader platform focus and commitment to a comprehensive feature set.

“Telmai has been recognized due to its innovative approach to data observability and its open architecture,” said Andrew Brust, Lead Analyst for Data, AI, and Analytics at GigaOm. “Having its own analytics and ML computation engine enables Telmai to observe data at scale without sampling or inordinate reliance on metadata, and opens the platform to monitor data quality across heterogeneous data systems.”