*>(dst + size - 16), _mm_loadu_si128(reinterpret_cast(src + size - 16))); Factual Clickhouse implementation as an exampleExample – memcpy: handcrafted 88 void *memcpy_ch(void * __restrict __m128i*>(src) + 6); c7 = _mm_loadu_si128(reinterpret_cast(src) + 7); src += 128; Factual Clickhouse implementation as an exampleExample – memcpy: handcrafted 89 void *memcpy_ch(void * __restrict return ret; } Factual Clickhouse implementation as an exampleExample – memcpy: handcrafted 90 Re-autovectorized, loops unrolled Still predominantly unaligned Factual Clickhouse implementation as an

An extended analytical engine for TiDB ○ Columnar storage and vectorized processing ○ Based on ClickHouse with tons of proprietary modifications ● Data sync via extended Raft consensus algorithm ○ Strong b 0 kevin 107 b 0 joe L0 L0 L1 L0 L1 L2 MutableMergeTree Storage Engine (Based on MergeTree of ClickHouse, LSM-Tree like design) In memory, rowbased (raft, transaction, cache) Versioned rows (MVCC)

defining. Competitors: TiDB feature similar optimizations to those that clickhouse has. These optimizations would normally make Clickhouse an ideal database solution for big data problems like registering

Co., Ltd. All rights reserved. Tag：统一的数据存储 InfluxDB DeepFlow 5.3 Elasticsearch DeepFlow 5.1 1x ClickHouse DeepFlow 5.7 3x 300x 100K 300K 100M DeepFlow的演进之路 (每秒列读写速率) InfluxDB+ DeepFlow 5.5 30x 2M 18mon