dbt-databricks VS QuestDB

Our current data infra looks a little something like this: 1. Airbyte deployed on EKS for supported data connectors. I’m using the alpha Databricks connector to load directly into Unity Catalog. 1a. S3 bucket for raw landing zone storage if we cannot directly load into Databricks Managed Tables. 2. Orchestration, storage, and transformations are in Databricks. Calling out to the Airbyte api in the EKS cluster to keep all orchestrations inside Databricks. 2a. databricks-dbt for transformations & cleaning.

dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA)

Read this https://github.com/databricks/dbt-databricks

Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose.

Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake.

databricks

Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward.

If your data lacks uniform time intervals between consecutive entries, QuestDB offers a solution by allowing you to sample your data. After that, MindsDB facilitates creating, training, and deploying your time-series models.

If you're interested in that functionality or have any other feedback, please drop by our open source repository or community Slack and let us know.

QuestDB is a high-performance time series database with SQL analytics that can power through market data ingestion and analysis. It's open source and integrates well with the tools and languages you use. Check us out!

Looks like full keys are always compared if hash codes test equal, which is what I'd expect. For example: https://github.com/questdb/questdb/blob/master/core/src/main...

But of course, I want to run a QuestDB instance on my node, which uses two additional TCP ports for Influx Line Protocol (ILP) and Pgwire communication with the database. So how can I expose these extra ports on my node and route traffic to the QuestDB container running inside of k3s?

In this post, I will detail a way in which I recently used annotations while writing an operator for my company's product, QuestDB. Hopefully this will give you an idea of how you can incorporate annotations into your own operators to harness their full potential.

QuestDB is an open source, high performance time series database. With its massive ingestion throughput speeds and cost effective operation, QuestDB reduces infrastructure costs and helps you overcome tricky ingestion bottlenecks. Thanks for reading!