Users can now pause their Tembo Cloud instances when they are not being used actively to save cost. This is most useful when running experiments and benchmarks.

Instances can also be resumed with a single click.

Documentation: https://tembo.io/docs/product/cloud/configuration-and-management/pause-instance

You can now run your Tembo Cloud instances on AWS Spot instances for 30% cheaper.

Spot instances are recommended for non-critical workloads which can tolerate upto 10 mins of occasional downtime when the spot instances get reclaimed. These are a perfect fit for dev instances or for workloads where retrying your queries in ~10 mins is an option.

Spot can be picked during instance provisioning or adjusted later in Instance settings.

Documentation: https://tembo.io/docs/product/cloud/configuration-and-management/spot-instances

Users can now change the names of their Tembo Cloud instances and the name of their org via the Tembo Cloud UI.

You can do so by going into Settings -> Instance Settings -> Name.

Read more in the documentation here: https://tembo.io/docs/product/cloud/configuration-and-management/rename-an-instance

Users can now visit https://status.tembo.io/ to check out the status of our cloud service.

Users can now view active and historical alerts for their Tembo instances. A wide variety of alerts are now visible including system resources, general database issues and Postgres specific ones.

Blog announcing the feature: https://tembo.io/blog/introducing-status-alerts

Documentation about all available alerts: https://tembo.io/docs/product/cloud/alerts

Users now can see a greater description of stacks when the spin up an instance. Also, they have a single click deploy for free button.

Allow users to export their data to S3 (as a low-cost storage option) and query it. Can be enabled by using the pg_tier extension which is now available on Tembo Cloud.

Link to pg_tier respository: https://github.com/tembo-io/pg_tier

The Sign up and Sign in pages on Tembo Cloud are now branded and don't use the default Clerk pages.

Go to Tembo Cloud (cloud.tembo.io) when not signed in to view.

Users can now use pganalyze to easily monitor and analyze their Tembo Cloud Postgres instances. They can get detailed insights into database performance and configure alerts to receive notifications about the same.

Launch blog: https://tembo.io/blog/pganalyze

Documentation: https://tembo.io/docs/product/cloud/apps/pganalyze

Time-series data is data which is organized along a time dimension and which typically grows via recent data being inserted in near real-time. Tembo’s Time Series stack makes the creation, operation, and maintenance of databases for storing time-series data simple. Follow the guide here to get started: https://tembo.io/docs/product/stacks/analytical/timeseries

Based on the open source extension: https://github.com/tembo-io/pg_timeseries

Stack for running long-running OLAP queries with compressed columnar storage.

Getting started guide: https://tembo.io/docs/tembo-stacks/olap/

Users can now choose between Postgres 14, 15, and 16 when deploying Tembo Cloud instances.

https://tembo.io/blog/postgres-14-and-16

Tembo CLI is the easiest way to try out Postgres extensions, stacks, and apps locally.

It also helps you deploy the same Tembo configuration across development, staging, and production environments. This means when you test locally, your workload behaves the same way when deployed to the cloud.

Launch blog: https://tembo.io/blog/tembo-cli

Docs: https://tembo.io/docs/tembo-cloud/Tembo-CLI/Getting_Started

The Tembo RAG stack allows you to natively build Q&A bots on Postgres. You can try it out on your own by using our Kubernetes Operator, deploy it with a single click on Tembo Cloud, or run it locally with docker-compose.

Launch blog: https://tembo.io/blog/tembo-rag-stack

Docs: https://tembo.io/docs/tembo-stacks/rag

MongoDB Alternative on Postgres stack allows you to run Mongo workloads directly on Postgres while keeping API compatibility with Mongo. This is powered in collaboration with FerretDB.

FerretDB launch blog: https://blog.ferretdb.io/run-mongodb-workloads-ferretdb-tembo/
Tembo launch blog: https://tembo.io/blog/mongo-on-postgres

Documentation: https://tembo.io/docs/tembo-stacks/mongo-alternative

The Tembo Geospatial stack is designed and optimized for running geospatial workloads in an easy manner on Postgres. It comes pre-packaged with PostGIS and other related extensions, allowing you to perform geospatial analysis without needing to set up another database!

Launch blog: https://tembo.io/blog/geospatial-on-postgres

Documentation: https://tembo.io/docs/tembo-stacks/geospatial

With Tembo Cloud, you can now have a seamless link to do vector search using over 120 open-source Sentence Transformers from Hugging Face, directly from Postgres.

This is powered by pg_vectorize, an open source extension. pg_vectorize is available by default on the Tembo VectorDB Stack in Tembo Cloud and can be added to any Tembo Postgres instance.

The Tembo VectorDB stack makes it easy to build classification, clustering, search and recommendation applications easily with Postgres. The stack contains our pg_vectorize extension which allows you to generate and autonomously updates embeddings in Postgres. You can also host any of 100+ sentence transformer models (demo) available on Huggingface, right next to your Postgres database for private, low-latency embeddings generation without using OpenAI credits.

Postgres optimized for data warehouse workloads

Launch blog post: https://tembo.io/blog/tembo-data-warehouse

Docs: https://tembo.io/docs/tembo-stacks/datawarehouse/

Stack for running ML Ops on Postgres powered by PostgresML

Launch blog post: https://tembo.io/blog/simplified-ml-ops
Docs: https://tembo.io/docs/tembo-stacks/machine-learning

Simple, easy-to-use message queue, no external tools or add-ons needed. (Even better, it's crazy fast.)

Launch blog post https://tembo.io/blog/mq-stack-benchmarking/

An Optimized open source stack designed to be an "all-in-one" OLTP database, easily customized to your specific use case.

https://tembo.io/blog/introducing-pg_vectorize

`prometheus_fdw` is an open source foreign data wrapper extension for Postgres. [View github project](https://github.com/tembo-io/prometheus_fdw).

New homepage release

Pricing & billing infrastructure, support SLA

Local instance creation, deploy to Tembo cloud via CLI

- Database status notifications and health monitoring

Stable API, object membership model, relaxed compiling requirements, unlogged queue type

Config improvements, RestAPI integration, and pgmq 1.0

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