July 2022 Summaries

Cube is transitioning from using Redis for queue and in-memory cache management to its proprietary Cube Store, aiming to enhance performance, scalability, and simplicity in its data applications. Although Redis has been effective, Cube's growing use cases and performance demands necessitate a more specialized solution. Cube Store will replicate Redis' functionality with improvements such as single atomic domain-specific instructions to reduce clashes and binary data storage for efficiency. This migration, set to be completed by mid-2023, promises better throughput and aligns with Cube's mission of providing consistent, secure, and performant data handling. Users can expect seamless integration as Cube Store will utilize the same SQL protocol as the current pre-aggregation management.

Hex is a modern data workspace that makes it easy to connect to data, analyze it in collaborative SQL and Python-powered notebooks, and share work as interactive data apps and stories. It provides three major elements: Logic View for developing analysis, App Builder for creating interactive apps with dynamic reports and dashboards, and Share Dialog for collaborating on analysis or exposing it as a publicly-accessible app. Cube is the headless BI platform that accesses data from modern data stores, organizes it into consistent metrics definitions, and delivers them to downstream applications, providing benefits such as data source support, data modeling, performance, and native SQL. By connecting Hex with Cube upstream, users can achieve consistent metrics definitions for their data analysis and data apps, making it easier to collaborate and share knowledge across teams.

This article demonstrates how to build analytics dashboards showing summaries of data stored in ClickHouse and how Cube can provide a semantic layer with high-level metrics definitions over raw data as well as a caching layer shielding your ClickHouse instance from repetitive requests by end users. ClickHouse is a column-oriented database optimized for online analytical data processing, which can easily handle trillions of data points in a single table. It integrates with various data sources, such as S3, Kafka, and relational databases, allowing you to ingest data into ClickHouse without using additional tools. Cube is the headless BI platform for accessing, organizing, and delivering data, connecting to many data warehouses, databases, or query engines, including ClickHouse. In this article, we demonstrate how to use Cube's REST and SQL APIs to build analytics dashboards, retrieve data from ClickHouse, and implement caching to scale the performance of high-traffic dashboards. The pipeline involves using Cube's caching mechanism to shield your ClickHouse instance from repetitive requests by end users, allowing you to focus on building more complex queries without worrying about performance issues. By using Cube with ClickHouse, you can create a scalable and flexible analytics platform that meets the needs of your business.