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AlloyDB Omni is a downloadable database software package that
lets you deploy a streamlined edition of AlloyDB for PostgreSQL in your own computing
environment. You can run AlloyDB Omni in private data centers,
on public clouds, and on developer laptops.
To get started with AlloyDB Omni, use the following guides,
which provide detailed information about how to install and use
AlloyDB Omni in virtual machine (VM) environments.
AlloyDB Omni doesn't include some AlloyDB for PostgreSQL features that
rely on operation within Google Cloud. If you want to upgrade your project to
the fully managed scaling, security, and availability features of
AlloyDB for PostgreSQL, you can migrate your
AlloyDB Omni data into an AlloyDB for PostgreSQL cluster like
any other initial data import.
Use cases
AlloyDB Omni is well-suited to the following scenarios:
You need a scalable and performant version of PostgreSQL, but you can't
run a database in the cloud due to regulatory or data sovereignty
requirements.
You need a database that keeps running even when it's disconnected from
the internet.
You want to physically locate your database as close as possible to your
users, in order to minimize latency.
You want to migrate away from a legacy database without committing to a
full cloud migration.
You have workloads that need to run in multiple public clouds, or in
a hybrid cloud with private data centers and public clouds intermixed.
What it's good for
AlloyDB Omni includes many of the performance improvements in
AlloyDB for PostgreSQL. AlloyDB Omni has more
than twice the throughput of open source
PostgreSQL on TPC-C-like tests with HammerDB, and it offers an improvement in
response time by up to a hundred times for TPC-H-like analytical queries.
AlloyDB Omni
also supports autopilot features from AlloyDB for PostgreSQL in
Google Cloud, allowing it to
self-update and self-tune. These autopilot features include automatic memory
management, adaptive autovacuum, and index advisor. AlloyDB Omni
also supports the columnar engine, which can accelerate analytical queries on
large data sets by up to 100 times.
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