This article is based on reporting originally published at cloudcomputing-news.net, covering Google’s June 2019 announcement of its intent to acquire Looker.
Google Announces $2.6 Billion Acquisition of Looker
In June 2019, Google announced its intention to acquire Looker, a cloud-based business intelligence (BI) and data analytics platform, for $2.6 billion in an all-cash transaction. Upon closing, Looker would join the Google Cloud portfolio. The deal positioned Google Cloud more aggressively in the enterprise analytics market, arriving around the same time Salesforce announced its much larger acquisition of Tableau.
For Google Cloud, the acquisition was framed as filling a critical gap: giving customers a more complete path from raw data ingestion to actionable business insights, all integrated with BigQuery, Google’s managed enterprise data warehouse.
Why Looker? Bridging the Gap Between Data and Decisions
Google Cloud CEO Thomas Kurian described the strategic rationale clearly: Looker would help deliver “a more complete analytics solution from ingesting data to visualising results and integrating data and insights into daily workflows.” In practical terms, this meant customers migrating from legacy data stacks to BigQuery would gain access to a mature BI layer without needing to bolt on third-party tooling.
Looker’s core value proposition — its LookML modelling layer and ability to connect to a wide range of data sources — made it a natural complement to BigQuery. Prior to the acquisition, the two companies had already established a meaningful partnership:
- Looker had announced a BigQuery integration enabling data teams to build machine learning models directly within BigQuery through the Looker interface.
- The two companies shared more than 350 mutual customers, including BuzzFeed, Hearst, and Yahoo!
The Multi-Cloud Commitment: A Strategic Differentiator
Perhaps the most significant aspect of the acquisition announcement — especially for enterprise customers already spread across multiple cloud providers — was Google’s explicit pledge to maintain Looker’s multi-cloud functionality.
Looker was already compatible with all major cloud databases and data warehouses at the time of the announcement, including:
- Amazon Redshift
- Microsoft Azure SQL
- Oracle
- Teradata
- Google BigQuery
Looker CEO Frank Bien confirmed that customers should expect continued support across all major cloud databases after the acquisition closed — a reassurance aimed directly at enterprises nervous about vendor lock-in.
Kurian reinforced this position in a public statement: “While we deepen the integration of Looker into Google Cloud Platform, customers will continue to benefit from Looker’s multi-cloud functionality and its ability to bring together data from SaaS applications like Salesforce, Marketo, and Zendesk, as well as traditional data sources. This empowers companies to create a cohesive layer built on any cloud database, as well as on other public clouds and in on-premise data centres.”
Context: Google Cloud’s Broader Open and Multi-Cloud Direction
The Looker acquisition did not happen in isolation. At Google Cloud Next in San Francisco in April 2019, the company’s central themes were hybrid cloud, multi-cloud, and open source. A notable moment from the keynote was the announcement of partnerships with seven open source database vendors, including Confluent, MongoDB, and Redis Labs.
Looker’s broad database compatibility aligned directly with this open, multi-cloud positioning — and gave Google Cloud a commercial BI product that could operate credibly across competitor infrastructure, rather than requiring customers to consolidate entirely onto GCP.
Industry Reaction
Industry analysts viewed the deal positively in the context of the fast-growing data analytics market. Frank Gens, Senior Vice President and Chief Analyst at IDC, commented: “Google Cloud is one of the leaders in the data warehouse market, and the addition of Looker will further strengthen their ability to serve the needs of enterprise customers while also advancing their commitment to multi-cloud.”
Kurian also addressed continuity of support: “Looker customers can rest assured that the high-quality support experience that Looker has provided will be bolstered by the resources, expertise, and global presence of our cloud team. We will also continue to support best of breed analytics and visualisation tools to provide customers the choice to use a variety of technologies with Google Cloud’s analytics offering.”
Key Takeaways for DevOps and Data Engineering Teams
- Multi-cloud BI is a viable strategy. Google’s commitment to keeping Looker database-agnostic acknowledged that most enterprises operate across more than one cloud, and analytics tooling must reflect that reality.
- BigQuery integration deepens. Teams already using BigQuery gained a tighter native path to Looker’s modelling and visualisation capabilities, including ML model creation directly within BigQuery.
- Vendor lock-in concerns are legitimate. Google’s explicit pledge to maintain cross-cloud support was a direct response to enterprise concern — it is worth monitoring how that commitment evolved post-acquisition.
- SaaS data connectivity matters. Looker’s ability to connect to SaaS sources such as Salesforce, Marketo, and Zendesk meant the platform addressed not just cloud warehouse data, but the broader operational data landscape.