They are modified for, and are dependent on, their environments. In some cases, these modifications may mean that PostgreSQL itself is forked to support optimizations to best make use of the cloud provider's architecture. One key consideration that every DBA should listen to intently, though, is that none of these options are purely community-distributed PostgreSQL, nor are they solely database-focused versions. The product of Microsoft’s acquisition of Citus Data, Hyperscale allows for more powerful growth model with horizontal scalability as a built-in deployment option. What does Microsoft Azure offer as a PostgreSQL database service?Īzure Database for PostgreSQL has similar features and caveats as Amazon’s offerings, though it also has Hyperscale as a deployment option. Aurora’s PostgreSQL flavor retains the same other differences we noted for RDS PostgreSQL itself as well. This is often touted as a stronger model for recovery times as well as a reduced traffic of IOPS, but it’s worth noting that the cost saved by this change is often overshadowed by the cost of the traffic of the six copies themselves. This is because the engine itself does not push down modified pages to the storage layer, and instead relies on an in-memory page caching model. You retain the benefits of RDS PostgreSQL, but acquire a version of PostgreSQL which has a highly-modified storage model which strongly favors applications which perform a high volume of queries and transactions at the same time. The advantages over plain RDS PostgreSQL are straightforward: storage is highly resilient, because even just a single Aurora instance carries six copies of the data, and these copies are distributed across three availability zones. It’s highly modified for performance and resilience. For many, these aren’t showstoppers, but they’re worth knowing before you make your choice.Īmazon Aurora with PostgreSQL CompatibilityĪurora’s PostgreSQL-Compatible Edition is a bit different. Finally, and more commonly-known, you don’t have access to the compute itself. Performance is also more limited, even if RDS does “make it easy”, because tweaks like WAL storage changes, pgpool or pgbouncer are out if you’re on RDS. It does allow you to use the DB parameter groups and database grants to handle these respective needs, but that means that any automation you use for a database in any other environment will require change. RDS does not allow you to directly edit the nf or pg_hba.conf files. There are, of course, some caveats to consider. IOPS make throughput needs straightforward for low-to-mid demand platforms. Features like Multi-AZ and snapshots are accomplished easily here and out-of-the-box here. Bit-for-bit, it’s not the same as PostgreSQL, but functionally-speaking, it’s a strong equivalent for the common use case. The former offers much of what you need: a quick-to-configure, easy-to-manage implementation of PostgreSQL.
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