The problem this tutorial is trying to solve is the lack of a native Fivetran connector for CockroachDB. My customer has built their analytics pipeline based on Fivetran. Given there is no native integration, their next best guess was to set up a Postgres connector:
CockroachDB is PostgreSQL wire compatible, but it is not correct to assume it is 1:1. Let’s attempt to configure the connector:
At its core Snowflake is a data platform. It’s not specifically based on any cloud service which means it can run any of the major cloud providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP). As a SaaS (Software-as-a-Service) solution, it helps organizations consolidate data from different sources into a central repository for analytics purposes to help solve Business Intelligence use cases.
Once data is loaded into Snowflake, data scientists, engineers, and analysts can use business logic to transform and model that data in a way that makes sense for their company. With Snowflake users can easily query data using simple SQL. This information is then used to power reports and dashboards so business stakeholders can make key decisions based on relevant insights.
SQL Server Analysis Services (SSAS) is used to create high-level aggregated views of data, allowing users to quickly create dynamic reports and dashboards to centralize business measurable values like Key Performance Indicators (KPIs).
In this article, we’ll cover how a user continued their analytics in SSAS after transferring terabytes of data into a Snowflake data warehouse.
Hybrid cloud architectures are the new black for most companies. A cloud-first is obvious for many, but legacy infrastructure must be maintained, integrated, and (maybe) replaced over time. Event Streaming with the Apache Kafka ecosystem is a perfect technology for building hybrid replication in real-time at scale.
Most enterprises require a reliable and scalable integration between legacy systems such as IBM Mainframe, Oracle, SAP ERP, and modern cloud-native applications like Snowflake, MongoDB Atlas, or AWS Lambda.
The benefits of building a DevOps culture in software companies are clear. DevOps practices integrate once-siloed teams across the software development lifecycle, from Dev to QA to Ops, resulting in both faster innovation and improved product quality. As a result, most software development teams have deployed tools to enable DevOps practices across their workflow.
The topic of database DevOps is trending right now and most Snowflake customers are asking about it, especially those who want to build a modern data platform in the cloud. But actually doing DevOps for a database environment is difficult and has some unique challenges compared with doing DevOps for applications.
