数据架构统一的必要性，主要在于数据重复建设带来的混乱低效，但实现的难点是不同场景的性能平衡点不同。
比如，对于一个数据平台而言，数据新鲜度、低成本、高性能不可能同时实现，而在不同的数据计算场景比如典型的批计算、流计算、交互式分析中，重视的性能平衡点也不同，比如批计算重成本优化，流计算重数据新鲜度，交互式分析重查询性能，这样在场景切换时底层架构难以一直保持最佳性能。所以，传统的做法是采用多套不同的架构的组合，也就是Lambda架构来达到最佳性能。
为打破架构之间的技术屏障，云器采用增量计算模型统一批、流、交互三种计算模式，通过“增量时间间隔”关键变量来灵活切换不同的计算模式，在大幅降低建设成本、精简架构的同时，保持稳定的最优性能。
欢迎参与DataFun联合云器科技在2023年12月19日举办的技术实践与原理分享会，一起推动数据架构一体化进程！
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