GCP – Google Cloud named a Leader in the 2024 Gartner Magic Quadrant for Data Integration Tools

We’re excited to share that Gartner has recognized Google as a Leader in the 2024 Gartner® Magic Quadrant™ for Data Integration Tools. As a Leader in this report, we believe Google’s position is a testament to delivering continuous customer innovation in areas such as unified data to AI governance, flexible and accessible data engineering experiences, and AI-powered data integration capabilities.

Today, most organizations operate with just 10% of the data they generate, which is often trapped in silos and disconnected legacy systems. The rise of AI unlocks the potential of the remaining 90%, enabling you to unify this data — regardless of format — within a single platform. 

This convergence is driving a profound shift in how data teams approach data integration. Traditionally, data integration was seen as a separate IT process solely for enterprise business intelligence. But with the increased adoption of the cloud, we’re witnessing a move away from legacy on-premises technologies and towards a more unified approach that enables various users to access and work with a more robust set of data sources. 

At the same time, organizations are no longer content with simply collecting data; they need to analyze it and activate it in real-time to gain a competitive edge.  This is why leading enterprises are either migrating to or building their next-gen data platforms with BigQuery, converging the world of data lakes and warehouses. BigQuery’s unified data and AI capabilities combined with Google Cloud’s comprehensive suite of fully managed services, empower organizations to ingest, process, transform, orchestrate, analyze, and activate their data with unprecedented speed and efficiency. This end-to-end vision delivers on the promise of data transformation, so businesses can unlock the full value of their data and drive innovation.

Choice and flexibility to meet you where you are

Organizations thrive on data-driven decisions, but often struggle to wrangle information scattered across various sources. Google Cloud tools simplify data integration, by letting you:  

• Streamline data integration from third-party applications – With BigQuery Data Transfer Service, onboarding data from third-party applications like Salesforce or Marketo becomes dramatically simplified, eliminating complex coding and saving valuable time and data movement costs. 

• Create SQL-based pipelines – Dataform helps create robust, SQL-based pipelines, orchestrating the entire data integration flow easily and scalably. This flexibility empowers organizations to connect all their data dots, wherever they are, so they can unlock valuable insights faster.

• Use gen-AI powered data preparation – BigQuery data preparation empowers analysts to clean and prepare data directly within BigQuery, using Gemini’s AI for intelligent transformations to streamline processes and help ensure data quality.  

Bridging operational and analytical systems

Data teams know how frustrating it can be to have valuable analytical insights trapped in a data warehouse, disconnected from the operational systems where they could make a real impact. You don’t want to get bogged down in the complexities of ELT vs. ETL vs. ETL-T — you need solutions that prioritize SLAs to ensure on-time and consistent data delivery. This means having the right connectors to meet your needs, especially with the growing importance of real-time data. Google Cloud offers a powerful suite of integrated tools to bridge this gap, helping you easily connect your analytical insights with your operational systems to drive real-time action. With Google Cloud’s data tools, you can:

• Perform advanced similarity searches and AI-powered analysis – Vector support across BigQuery and all Google databases lets you perform advanced similarity searches and AI-powered analysis directly on operational data. 

• Query operational data without moving it – Data Boost enables analysts to query data in place across sources like Bigtable and Vertex AI, while BigQuery’s continuous queries facilitate reverse ETL, pushing updated insights back into operational systems. 

• Implement real-time data integration and change data capture – Datastream captures changes and delivers them with low latency. Dataflow, Google Managed Service for Kafka, Pub/Sub, and new support for Apache Flink further enhance the reverse ETL process, fueling operational systems with fresh, actionable insights derived from analytics, all while using popular open-source software.  

Governance at the heart of a unified data platform

Having strong data governance is critical, not just a checkbox item. It’s the foundation of ensuring your data is high-quality, secure, and compliant with regulations. Without it, you risk costly errors, security breaches, and a lack of trust in the insights you generate. BigQuery treats governance as a core component, not an afterthought, with a range of built-in features that simplify and automate the process, so you can focus on what matters most — extracting value from your data.

• Easily search, curate and understand data with accelerated data exploration – With BigQuery data insights powered by Gemini, users can easily search, curate, and understand the data landscape, including the lineage and context of data assets. This intelligent discovery process helps remove the guesswork and accelerates data exploration. 

• Automatically capture and manage metadata – BigQuery’s automated data cataloging capabilities automatically capture and manage metadata, minimizing manual harvesting and helping to ensure consistency. 

• Manage and govern data across different storage systems – Dataplex automatically generates BigLake and Object tables at scale, making it easier to manage and govern data across different storage systems and get value from unstructured data.

Intelligent data experiences powered by Gemini 

Google Cloud’s infrastructure is purpose-built with AI in mind, allowing users to easily leverage generative AI capabilities at scale. Users can train models, generate vector embeddings and indexes, and deploy data and AI use cases without leaving the platform. AI is infused throughout the user journey, with features like Gemini-assisted natural language processing, secure model integration, AI-augmented data exploration, and AI-assisted data migrations. This AI-centric approach delivers a strong user experience for data practitioners with varying skill sets and expertise.

What’s next

We’re honored to be recognized as a Leader in the 2024 Gartner Magic Quadrant for Data Integration Tools. We look forward to continuing to innovate and partner with you on your data transformation journey. Download the complimentary 2024 Gartner Magic Quadrant for Data Integration Tools report today.

_{2024 Gartner Magic Quadrant for Data Integration Tools -Thornton Craig et al, December 3, 2024. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Google. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.}