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Amazon Bedrock smooths the path to building generative AI apps with prompt engineering and RAG, providing a good assortment of text, chat, and image-based foundation models.
Azure AI Studio, while still in preview, checks most of the boxes for a generative AI application builder, with support for prompt engineering, RAG, agent building, and low-code or no-code development.
Here's a first look at the developer preview of Cosmonic—a WebAssembly PaaS with its own graphical cloud user interface, robust networking, and CLI.
Google Cloud Dataplex is an amazingly complete system for turning raw data from silos into unified data products ready for analysis. And a bit overwhelming to learn.
Ballerina was designed to simplify the development of distributed microservices by making it easier to integrate APIs. For C, C++, C#, and Java programmers, much will feel familiar.
Dremio Cloud leaps big data in a single bound with a fast SQL engine and optimizations that can accelerate queries dramatically. Plus it lets you use other engines on the same data.
Kissflow has a good selection of low-code and no-code development capabilities, along with useful integrations with external systems for handling events and performing automations.
Snowpark for Python gives data scientists a nice way to do DataFrame-style programming against the Snowflake data warehouse, including the ability to set up full-blown machine learning pipelines to run on a recurrent schedule.
YugabyteDB 2.13 is a highly scalable, distributed version of PostgreSQL that combines compelling ideas from Google Cloud Spanner and Amazon Aurora—and serves as a Cassandra-compatible database too.
Databricks Lakehouse Platform combines cost-effective data storage with machine learning and data analytics, and it's available on AWS, Azure, and GCP. Could it be an affordable alternative for your data warehouse needs?