List of Databricks Delta Lake UniForm Customers
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Since 2010, our global team of researchers has been studying Databricks Delta Lake UniForm customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Databricks Delta Lake UniForm for AI Database from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Databricks Delta Lake UniForm for AI Database include: AT&T, a United States based Communications organisation with 146040 employees and revenues of $122.43 billion, Nasdaq, a United States based Banking and Financial Services organisation with 9162 employees and revenues of $4.65 billion, Bringme, a Belgium based Professional Services organisation with 100 employees and revenues of $9.0 million and many others.
Contact us if you need a completed and verified list of companies using Databricks Delta Lake UniForm, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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AT&T | Communications | 146040 | $122.4B | United States | Databricks | Databricks Delta Lake UniForm | AI Database | 2024 | n/a | In 2024, AT&T implemented Databricks Delta Lake UniForm within its data platform in the United States, using the AI Database to improve interoperability across data and AI assets. AT&T cited Databricks' open-sourcing of Unity Catalog as supporting interoperable tools and consistent governance for its data platform, and the Databricks messaging links Unity Catalog capabilities to UniForm usage for cross-format coordination. The deployment centers on Unity Catalog driven metadata and governance layered over Delta and Iceberg table formats, enabling cataloging, consistent access controls, and unified metadata management. Databricks Delta Lake UniForm is positioned to provide interoperability between Delta and Iceberg, supporting standard functional workflows for data discovery, schema enforcement, and controlled access across heterogeneous storage formats. Operational coverage is the AT&T data platform in the United States, with functional impact on data engineering, analytics, and AI teams that depend on shared metadata and toolchain interoperability. Governance emphasis focused on consistent policies and interoperable tooling enabled by the open-sourced Unity Catalog, which AT&T cited as the rationale for the UniForm alignment and for improving cross-tool and cross-format governance across its data and AI assets. | |
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Bringme | Professional Services | 100 | $9M | Belgium | Databricks | Databricks Delta Lake UniForm | AI Database | 2018 | n/a | In 2018, Bringme implemented Databricks Delta Lake UniForm as an AI Database to centralize analytical and machine learning datasets. Bringme is a Belgium based professional services company with approximately 100 employees, and the deployment focused on creating a single source of truth for data engineering and analytics workflows. Databricks Delta Lake UniForm was configured to deliver transactional delta tables with schema enforcement and ACID semantics, enabling both batch and streaming ingestion patterns and repeatable ETL pipelines. The implementation emphasized notebook driven data preparation, job orchestration for scheduled pipelines, and metadata management to standardize feature extraction and model training artifacts. Operational coverage concentrated on data engineering and analytics functions to support enterprise reporting and AI model development, with environment separation for development and production. Governance controls were implemented through access control and lineage tracking to enforce data quality and reproducibility across analytics workflows. | |
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Nasdaq | Banking and Financial Services | 9162 | $4.6B | United States | Databricks | Databricks Delta Lake UniForm | AI Database | 2024 | n/a | In 2024, Nasdaq stated it leverages Databricks Unity Catalog as part of a United States data management strategy, and Databricks Delta Lake UniForm is inferred to provide Iceberg compatibility that enables cross-format interoperability. The public statement emphasizes eliminating data silos and scaling platform governance across Nasdaq's analytics and data engineering functions. Databricks Delta Lake UniForm, framed here as an AI Database capability, is inferred to deliver interoperability between Delta Lake and Apache Iceberg table formats through Unity Catalog compatibility. Typical implementation patterns consistent with this configuration include unified metadata management, centralized access controls and policy enforcement, and standardized lineage capture to support governance at scale. These functional capabilities align with Nasdaq's cited goals of reducing siloed datasets and creating a single control plane for data assets. Databricks' press release quotes Nasdaq on interoperability and governance benefits, which supports the inference that Databricks Delta Lake UniForm underpins Iceberg compatibility within Unity Catalog for Nasdaq in the United States. The implementation narrative centers on catalog-driven governance, catalog and format interoperability, and data platform consolidation across analytics and data engineering teams. |
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