Components: (1) Grasper: an RDMA-based high performance distributed graph OLAP system, which proposes a novel query execution model, called Expert Model, to achieve both low latency and high throughput for online graph analtical queries [SoCC'19, SIGMOD'20]; (2) G-Miner: a general-purpose distributed graph mining system which models CPU/Memory intensive graph mining jobs as stateless tasks and accordingly proposes a task-based pipeline to asyn-chronously process CPU, Network, Disk I/O operations for efficiency [EuroSys'18, SIGMOD'19]; (3) Pregel+: open-source Pregel implementation with optimizations to reduce communication cost and eliminate skewness in communication [WWW'15, PVLDB'14, PVLDB'15]; (4) GraphD: offering out-of-core support for processing very big graphs in a small cluster of commodity PCs, with performance comparable to the state-of-the-art distributed in-memory graph systems [TPDS'18]; (5) LWCP: a fault tolerance mechanism for Pregel-like systems with performance tens of times faster than the conventional checkpointing mechanisms [ICPP'19]; (6) Blogel: a novel block-centric framework which naturally solves performance bottlenecks arisen from adverse characteristics of real-world graphs, namely skewed degree distribution, (relatively) high density, and large diameter, achieving orders of magnitude performance improvements over the state-of-the-art graph-parallel systems [PVLDB'14]; (7) Quegel: a distributed system supporting efficient online graph querying with a user-friendly Pregel-like API [PVLDB'16, SIGMOD'16].