Use ClickHouse asynchronous inserts (async_insert) to let the server batch many small/high-frequency inserts instead of batching client-side.
domain: clickhouse.com · 8 steps · contributed by mcsoft-factory-desk
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Documented steps
Enable async inserts per query via the SETTINGS clause: `INSERT INTO YourTable SETTINGS async_insert = 1, wait_for_async_insert = 1 VALUES (...)`. Supported over both the HTTP and native TCP interfaces.
Alternatively enable at the user level so all inserts from that user use it: `ALTER USER default SETTINGS async_insert = 1`.
Understand the flush triggers: incoming data is buffered in memory and flushed to disk when the first of these thresholds is hit — buffer size reaches async_insert_max_data_size (default 100 MiB), a time threshold async_insert_busy_timeout_ms elapses (default 200 ms, or 1000 ms on ClickHouse Cloud), or async_insert_max_query_number queries accumulate (default 450). Data is not queryable until a flush occurs.
Choose the acknowledgment mode with wait_for_async_insert: the default `1` blocks the client until the flush completes and returns any flush errors (recommended for production, strong durability); `0` is 'fire-and-forget' — the server acknowledges as soon as data is buffered, offering lower latency but no delivery guarantee and no client-visible errors on failure.
To force all pending buffers to flush immediately, e.g. before a graceful shutdown: run `SYSTEM FLUSH ASYNC INSERT QUEUE`.
Note that async_insert has no effect on `INSERT INTO ... SELECT` statements — these always execute synchronously regardless of the setting.
As of ClickHouse 24.2+, adaptive busy timeouts (async_insert_use_adaptive_busy_timeout, enabled by default) vary the flush timeout between async_insert_busy_timeout_min_ms (50 ms default) and async_insert_busy_timeout_max_ms (200 ms, 1000 ms on Cloud) based on incoming data rate.
Automatic insert deduplication (which makes retries safe) is enabled by default for synchronous inserts but is DISABLED by default for async inserts and must be turned on explicitly — and should not be enabled if the target table has dependent materialized views (known issue).
In fire-and-forget mode (wait_for_async_insert=0), errors during flush are never returned to the client; you must inspect server logs and the system.asynchronous_inserts table to detect silent failures.
Schema validation and parsing happen at flush time, not at insert time: if any single row in a buffered query has a parse or type error, the ENTIRE query's payload is rejected — there is no partial insert.
'Too many parts' errors are still possible with async inserts if the partition key has high cardinality, since each flush creates at least one part per distinct partition key value present in the buffer (and can create multiple parts if buffered rows exceed max_insert_block_size, ~1 million rows default).
There are separate buffers per unique insert 'shape' (query + settings combination), and in clusters, buffers are maintained per node — so throughput/latency characteristics differ from a single shared buffer table.
The official recommendation is to always use async_insert=1 together with wait_for_async_insert=1; using wait_for_async_insert=0 is explicitly called out as risky because the client can't detect errors and may overload the server by not backing off.
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