After the 29th of February, 2024, all IBM Cloud Databases for PostgreSQL instances that are still running will be disabled. This will take place globally.
Users are expected to be on the most recent versions of PostgreSQL, or they must purchase the preferred version of IBM Cloud Databases for PostgreSQL, which includes all of the fantastic capabilities added to version 15.
Customers do not need to update their databases through any of the major versions that came before it in order to upgrade to the most recent version of PostgreSQL. Customers’ PostgreSQL 11 databases, for instance, can be upgraded directly to PostgreSQL 15 without any intervening steps.
Version 15 of IBM Cloud Databases for PostgreSQL is regarded to as the “Preferred” version, and as such, we strongly advise all of our clients to go with this particular option.
Customers are able to upgrade their database instances by using the documentation that is provided here.
Improve the quality of your database
Customers have the option of upgrading their databases with a solution that has little downtime by using read replicas, or they can use backup and restore. Here you may learn more about the upgrade pathways available for IBM Cloud Databases for PostgreSQL.
Customers are strongly encouraged to adopt the Read Replica technique because it has less of an impact and provides the opportunity to practice running the update without actually installing it.
PostGIS version 3.3 is now supported by IBM Cloud Databases for PostgreSQL
Support for PostGIS major version 3.3 has been added to IBM Cloud Databases for PostgreSQL versions 12 and higher. On February 29, 2024, previous versions of PostGIS version 2.x will be deprecated because they are no longer supported. Upgrades to PostGIS 3.3 can be performed by users with the help of the documentation that is provided below.
Before you may upgrade your database deployment, PostgreSQL version 11 must first have PostGIS upgraded to version 3.3. If you are using PostGIS with PostgreSQL version 11, you must upgrade PostGIS.
[…] Second, join bitmaps use sideways information passing to make sampling-based features consistent across joins. Both ideas can be adapted to handle data updates, they conclude. The paper generalizes across workloads and databases better than previous works. Using our techniques on a simple workload (JOBLight-train) with 40𝑘 synthetic queries of up to 3 tables, our model can generalize to the more complex Join Order Benchmark, which includes queries with up to 16 tables, and improve query runtimes by 2× over PostgreSQL. […]
[…] in order to provide your development and IT teams with the assistance they need in order to upgrade with confidence and unleash the new capabilities. In addition to the technical documentation that […]
[…] embeddings generation using a PostgreSQL function introduced by AlloyDB AI to create embeddings on your data. You can access Google’s […]