This content, written by Joel McKelvey, was initially posted in Looker Blog on Jan 16, 2020. The content is subject to limited support.
Database and data warehousing technologies are evolving at a tremendous pace. Businesses are increasingly diversifying their critical data across multiple databases to remain competitive and capture the technical innovation each database vendor provides. With data modernization (and digital transformation), a key initiative for many organizations, leveraging the power of databases — particularly massively parallel processing cloud-based databases — is the new normal.
Looker supports the database you choose
The Looker data platform can support whatever database (or databases) your business uses through pre-integrations with both cloud and on-prem systems. Looker does this in part by communicating directly with your database or data warehouse using SQL.
Looker helps businesses:
Most databases communicate in slightly different versions of SQL, called “dialects.” As a result, writing queries across multiple databases and multiple clouds can be frustrating and time-consuming for data teams. SQL dialects also contribute to the difficulties of database migration, resulting in the need to rewrite or debug significant amounts of SQL code.
Looker simplifies queries and masks the complexity of database dialects by automatically generating SQL queries on behalf of users. Looker also refines each SQL query to improve performance, saving time and resources. With more than 50 SQL dialects supported, you’ll be able to extract the most benefit out of whatever database your business chooses.
“At Namely, data security and privacy are extremely important to us, and so is the database we choose. With Looker, we don’t need to rewrite all our queries to make them work with a new database. Looker helps us focus on putting data in the hands of users, wherever it’s located.” — Jessica Ray, Sr. Product Manager, Reporting & Analytics, Namely
Make the most of your database’s SQL query engine
Looker provides in-database query processing. When a user is exploring data in Looker or running a query, the query is actually processed outside Looker by the database’s SQL query engine. In other words, your query is leveraging the database’s performance and capabilities — and will scale and perform in parallel with your database’s capabilities.
Looker issues a request in highly performant SQL to the database, which then processes the request and returns the result to Looker. Looker formats the result, and users can then employ Looker to deliver that result as a report, schedule, or action anywhere they want.
Did you know?
In a recent of public cloud users, 81% of respondents said they are working with two or more database providers1.
“We are proud to partner with Looker to provide our customers with powerful modern data infrastructure on-premises or in the cloud environment of their choosing. Together we’re helping our customers realize the true value of their data virtually anywhere and at any scale.” — Jason Wakeam, VP Business Development and Alliances, MemSQL
Looker supports 50+ SQL dialects (and many more databases)
Looker works with over 50+ SQL dialects and connects to a wide range of common databases, data warehouses, and data virtualization systems. Here are a few popular ones:
To view a complete list of supported databases and SQL dialects and learn more about connecting Looker to the database of your choice, read our full .
Learn more about Looker and how we support the that works best for your business.
1 Gartner Why Organizations Choose a Multicloud Strategy, Laurence Goasduff, May 7, 2019