Google Cloud introduces AlloyDB Omni, a downloadable version of AlloyDB that runs anywhere. In addition, improvements and a new pricing model for BigQuery are announced.

Even in the changing business climate, the needs of companies have never been as clear as they are today, the cloud provider writes in the press release. At the Google Cloud Data Cloud & AI Summit that took place today, everything revolves around optimizing the cost efficiency of data management. Google Cloud is making a series of announcements aimed at helping companies get more value from their data at a lower cost.

Get rid of legacy systems

Last spring, Google Cloud announced AlloyDB, a database management system built on top of the open-source PostgreSQL platform. With AlloyDB, Google Cloud wants to give companies a springboard to free critical workloads from legacy systems and move them to the cloud. As this is not always possible due to legal requirements or certain workloads perform better in an edge environment, Google builds on AlloyDB with the introduction of AlloyDB Omni.

This is a downloadable version that Google Cloud says runs in any environment, whether local, on the Edge, or on developers’ work laptops. Outside the cloud, AlloyDB still offers 2X faster processing for transactional workloads than standard PostgreSQL applications and 100X faster processing for analytical queries.

Organizations looking to migrate their workloads to a PostgreSQL database can use the database migration utility. “Google Cloud wants to be where customers need us most,” Andi Gutmans told SiliconAngle.

Reduce data costs

In tough economic times, companies look for every opportunity to increase their operational efficiencies. To offer more flexibility, Google Cloud announces a new business model around BigQuery. Typically, BigQuery comes in three plans: Standard, Enterprise, and Enterprise Plus.

From now on, customers can choose which functionalities they need from the various packages à la carte. In this way, you can put together the optimal price-performance mix and you only pay for the computing power that you actually use. BigQuery also leverages the power of a serverless architecture to provision additional capacity in granular increments, so underutilized capacity doesn’t add to costs.

BigQuery itself also gets some innovations. Users will soon be able to use the platform to set up their own data clean rooms. This is a controlled environment that anonymizes and aggregates sensitive data according to compliance rules. Data clean rooms are interesting for organizations that are bound by stricter data protection rules.

Additionally, BigQuery extends AI and ML capabilities by collaborating with DataRobot, Neo4j, and ThoughtSpot. For a complete rundown of all Google Cloud announcements, see this blog.