Why is Clickhouse slower than PostgreSQL?

Question

I want to use Clickhouse as an OLAP and PostgreSQL as an OLTP database.

The problem is that queries to Clickhouse run slower than on Postgres. The query is as below:

select count(id) from {table_name}

Here is my table structure:

CREATE TABLE IF NOT EXISTS {table_name} 
        (
            `id` UInt64,
            `label` Nullable(FixedString(50)),
            `query` Nullable(text),
            `creation_datetime` DateTime,
            `offset` UInt64,
            `user_is_first_search` UInt8,
            `user_date_of_start` Date,
            `usage_type` Nullable(FixedString(20)),
            `user_ip` Nullable(FixedString(200)),
            `who_searched_query` Nullable(FixedString(15)),
            `device_type` Nullable(FixedString(20)),
            `device_os` Nullable(FixedString(20)),
            `tab_type` Nullable(FixedString(20)),
            `response_api_type` Nullable(FixedString(20)),
            `total_response_time` Float64,
            `retrieved_instant_answer` Nullable(FixedString(100)),
            `is_relative_instant_answer` UInt8,
            `meta_search_instant_answer_type` Nullable(FixedString(50)),
            `settings_alignment` Nullable(FixedString(20)),
            `settings_safe_search` Nullable(FixedString(30)),
            `settings_search_results_number` Nullable(FixedString(30)),
            `settings_proxy_image_urls` Nullable(FixedString(30)),
            `cache_hit` Nullable(FixedString(20)),
            `net_status` Nullable(FixedString(20)),
            `is_transitional` UInt8
        )
        ENGINE = MergeTree() PARTITION BY creation_datetime ORDER BY (id)

I created an index on datetime field in both database and then ran optimize query on both. can anyone tell me why Clickhouse is slower than Postgres?

Answer 1

Finally I found the what I did wrong. I should not have made partition by datetime field. I created the table without partition and it got so much faster.