Best Data Engineering Tools in the UK

DataBuck enables data engineering teams to automate data profiling, quality validation, anomaly detection, and source-to-target reconciliation across modern data platforms. It enables AI-powered rule recommendations that surface missing values, duplicates, invalid formats, schema drifts, and distribution shifts. Non-uniform column relationships with no need to manually code each validation rule. Row and cell matching confirms that data ingestion, transformations, and cloud migrations are happening as expected. It works with Databricks, Snowflake, BigQuery, Oracle, SQL Server, dbt, and Airflow. Through deep integration into data engineering workflows, teams can surface data issues more quickly within hours, investigate and remediate mismatched data, and reduce time spent on repetitive, error-prone SQL queries.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

Composable is an enterprise-grade DataOps platform built for business users that want to architect data intelligence solutions and deliver operational data-driven products leveraging disparate data sources, live feeds, and event data regardless of the format or structure of the data. With a modern, intuitive dataflow visual designer, built-in services to facilitate data engineering, and a composable architecture that enables abstraction and integration of any software or analytical approach, Composable is the leading integrated development environment to discover, manage, transform and analyze enterprise data.

Consume data from any database, organize it into consistent metrics, and use it with every app. Build your Data and Reporting APIs faster with automated SQL generation, query optimization, access control, consistent metrics definitions, and API design. It takes only days to wrap any data source with a single reference Data API and simplify access to reporting and analytics data across your teams. Make it easy for data engineers and application developers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review and configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling AP Ready-to-use Report Builder and JavaScript components for charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. And you will not have to make custom report queries anymore!

Domo’s AI and data platform business is now part of Progress Software. Domo's cloud-native AI data readiness platform complements and significantly broadens Progress' data platform offerings, creating powerful synergies to deliver innovative, secure and scalable AI data readiness solutions worldwide. Together, these capabilities will help customers turn fragmented enterprise data and knowledge into governed, AI-ready intelligence, improving the security, governance and cost of AI-powered initiatives. Domo is the agentic platform for the intelligent enterprise, helping organizations connect, govern, activate, and distribute data and AI. Domo works with cloud data platforms including Snowflake, BigQuery, and Databricks to turn governed data into AI agents, apps, workflows, dashboards, and analytics. Its data foundation, activation, and distribution layers help teams build and deliver intelligence where work happens, with governance, security, and access controls across data and AI.

Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation. Looker is reinventing business intelligence for the modern company. Looker works the way the web does: browser-based, its unique modeling language lets any employee leverage the work of your best data analysts. Operating 100% in-database, Looker capitalizes on the newest, fastest analytic databases—to get real results, in real time.

Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems.

Archon Data Store is a next-generation enterprise data archiving platform designed to help organizations manage rapid data growth, reduce legacy application costs, and meet global compliance standards. Built on a modern Lakehouse architecture, Archon Data Store unifies data lakes and data warehouses to deliver secure, scalable, and analytics-ready archival storage. The platform supports on-premise, cloud, and hybrid deployments with AES-256 encryption, audit trails, metadata governance, and role-based access control. Archon Data Store offers intelligent storage tiering, high-performance querying, and seamless integration with BI tools. It enables efficient application decommissioning, cloud migration, and digital modernization while transforming archived data into a strategic asset. With Archon Data Store, organizations can ensure long-term compliance, optimize storage costs, and unlock AI-driven insights from historical data.

With ready access to the richest flexible semantic layer, explainable AI, and reusable data modeling, data engineers and scientists can be 95% more productive — create and expand semantic data models, understand any data interrelationship, and run federated queries to speed time to insight. Stardog offers the most advanced graph data virtualization and high-performance graph database — up to 57x better price/performance — to connect any data lakehouse, warehouse or enterprise data source without moving or copying data. Scale use cases and users at lower infrastructure cost. Stardog’s inference engine intelligently applies expert knowledge dynamically at query time to uncover hidden patterns or unexpected insights in relationships that enable better data-informed decisions and business outcomes.

Decube is a data management platform that helps organizations manage their data observability, data catalog, and data governance needs. It provides end-to-end visibility into data and ensures its accuracy, consistency, and trustworthiness. Decube's platform includes data observability, a data catalog, and data governance components that work together to provide a comprehensive solution. The data observability tools enable real-time monitoring and detection of data incidents, while the data catalog provides a centralized repository for data assets, making it easier to manage and govern data usage and access. The data governance tools provide robust access controls, audit reports, and data lineage tracking to demonstrate compliance with regulatory requirements. Decube's platform is customizable and scalable, making it easy for organizations to tailor it to meet their specific data management needs and manage data across different systems, data sources, and departments.

World's largest team of Functional Programming and Fast Data engineers focused on creating customized high-performance solutions. We move from "thought" to "thing" via rapid prototyping and proof of concept. Activate an ecosystem to deliver at scale with CI/CD to support your requirements. Understanding the strategic intent and stakeholder needs to develop a shared vision. Deploy MVP to launch the product in the most efficient & expedient manner possible. Continuous improvements and enhancements to support new requirements. Building great products and providing unmatched engineering services would not be possible without the knowledge and extensive usage of the latest tools and technology. We help you to capitalize on opportunities, respond to competitive threats, and scale successful investments by reducing organizational friction from your company’s structures, processes, and culture. Knoldus helps clients identify and capture the most value and meaningful insights from data.

Profile, cleanse, match and deduplicate data in drag-and-drop rules studio. Lo-code UI means no programming skill required, putting power in the hands of subject matter experts. Add AI & machine learning to your existing data management processes In order to reduce manual effort and increase accuracy, providing full transparency on machine-led decisions with human-in-the-loop. Offering award-winning data quality and matching capabilities across multiple industries, our self-service solutions are rapidly configured within weeks with specialist assistance available from Datactics data engineers. With Datactics you can easily measure data to regulatory & industry standards, fix breaches in bulk and push into reporting tools, with full visibility and audit trail for Chief Risk Officers. Augment data matching into Legal Entity Masters for Client Lifecycle Management.

Aggregate disparate data at scale, reliably and accurately, to make better business decisions with Switchboard, a data engineering automation platform driven by business teams. Uncover timely insights and accurate forecasts. No more outdated manual reports and error-prone pivot tables that don’t scale. Directly pull and reconfigure data sources in the right formats in a no-code environment. Reduce your dependency on the engineering team. Automatic monitoring and backfilling make API outages, bad schemas, and missing data a thing of the past. Not a dumb API, but an ecosystem of pre-built connectors that are easily and quickly adapted to actively transform raw data into a strategic asset. Our team of experts has worked in data teams at Google and Facebook. We’ve automated those best practices to elevate your data game. A data engineering automation platform with authoring and workflow processes proven to scale with terabytes of data.

Roseman Labs enables you to encrypt, link, and analyze multiple data sets while safeguarding the privacy and commercial sensitivity of the actual data. This allows you to combine data sets from several parties, analyze them, and get the insights you need to optimize your processes. Tap into the unused potential of your data. With Roseman Labs, you have the power of cryptography at your fingertips through the simplicity of Python. Encrypting sensitive data allows you to analyze it while safeguarding privacy, protecting commercial sensitivity, and adhering to GDPR regulations. Generate insights from personal or commercially sensitive information, with enhanced GDPR compliance. Ensure data privacy with state-of-the-art encryption. Roseman Labs allows you to link data sets from several parties. By analyzing the combined data, you'll be able to discover which records appear in several data sets, allowing for new patterns to emerge.