As a developer tools analyst, I've compared Project A (Pinterest's Querybook) and Project B (Redpanda Data's Connect) based on momentum, community size, and apparent use cases for the benefit of senior engineers. **Momentum and Community Size**: Project B (Connect) boasts significantly higher overall community engagement with 8,612 stars, compared to Project A's (Querybook) 2,249 stars. However, the recent activity (last 30 days) tells a more balanced story: Querybook garnered 12 new stars versus Connect's 6, suggesting a slight uptick in Querybook's momentum despite its smaller community. **Apparent Use Cases**: Querybook is positioned as a Big Data Querying UI, integrating table metadata management with a notebook interface, catering to data analysts and scientists for ad-hoc queries and exploratory data analysis. In contrast, Connect is focused on stream processing, aiming to simplify the operational aspects of complex, real-time data pipelines, which appeals to engineering teams dealing with high-throughput, low-latency applications. Both projects serve distinct niches within the data processing ecosystem, with Querybook focusing on interactive data exploration and Connect on streamlined stream processing operations. Engineers should choose based on whether their needs align more closely with big data querying (Querybook) or operational stream processing (Connect).