Today, Confluent, the data streaming pioneer, is excited to announce its entrance into MongoDB’s new AI Applications Program (MAAP). MAAP is designed to help organizations rapidly build and deploy modern generative AI (GenAI) applications at enterprise scale.

Snowflake combines unmatched scalability, performance, and ease of use. It simplifies the complexities of traditional data warehousing, enabling businesses to store and analyze data at scale without the overhead of infrastructure management. But to truly unlock the power of Snowflake, businesses need an efficient and secure way to move data into it.

Do you have a DB2 database that needs a REST API? Now you can connect to your IBM DB2 with DreamFactory in just a few minutes. In this short blog post I’ll explain how you can connect to DB2 with DreamFactory’s auto-generated REST API for DB2.

ClickHouse is a high-performance, columnar database designed for analytics and big data applications. One of ClickHouse's standout features is its ability to perform filtering directly on compressed data, enabling faster results compared to traditional relational databases. While working with ClickHouse, you will often encounter the WHERE and PREWHERE clauses, both of which are used to filter data. But what is the difference between WHERE and PREWHERE, and when should you use one over the other?

In today's data-driven landscape, data analysts rely on powerful database management tools to organize, query, and extract insights from vast datasets. With a multitude of options, choosing the right tool can significantly impact efficiency and performance. Tools like MySQL Workbench, SQL Server Management Studio, and Google BigQuery provide robust platforms for relational data management, while options such as MongoDB Compass cater to unstructured data needs.

Snowflake customers can take advantage of Fivetran’s data movement and data replication capabilities as a native application available in the Snowflake Marketplace.

Bigtable provides the query latency that real-time systems need when using data from BigQuery via the EXPORT DATA to Bigtable (reverse ETL) function.

Replicating databases in regulated environments starts with syncing data sources while ensuring the data never leaves the secure perimeter of the cloud or on-premises network.

N+1 queries are a frequent issue in complex applications built with Elixir and Phoenix. These queries can silently degrade application performance, often going unnoticed until they've compounded into a significant problem. They can substantially increase web page load times, as each additional query adds overhead to a database, consuming more time and resources. That's why it's crucial to detect and resolve N+1 queries to optimize production systems.