ClickHouse vs Alopex Skulk

What ClickHouse is

ClickHouse is a column-oriented SQL database for online analytical processing (OLAP). It is offered as open source and as a cloud service, and its official documentation includes a guide for time-series use.

How it works

MergeTree: the main table engine. Each insert creates a part sorted by the primary key, and a background process merges it with other parts.
Date and time types: types such as DateTime and DateTime64 for time-series columns.
Server: applications connect to the ClickHouse server and query with SQL.

Main features

SQL for OLAP.
TTL that removes expired data based on a time column.
Functions that round times to units such as hours or days for aggregation.

Limits

ClickHouse runs as a server separate from the application. As an analytics database that is not limited to time series, time-series handling is built from table design and SQL.

How it differs from Alopex Skulk

Both store data in columnar form and aggregate by time with SQL.

Alopex Skulk is a time-series engine written in Rust that grows from embedded to server to cluster on the same engine. Start small by embedding it in your application, then move the same application to a server with Prometheus-compatible endpoints and to a cluster that scales out with sharding and replication. In every form it ingests time series, queries them with PromQL and SQL, stores them in time-partitioned, columnar Parquet files, and drops expired partitions automatically. Time-series ingestion and PromQL are built in, and it runs inside the application, as a server or as a cluster.

Try Alopex Skulk to grow ingestion, retention and PromQL in one engine from your application to a cluster. Start from Alopex Skulk.

References

What is ClickHouse?, Time-series with ClickHouse, Date and time data types, Basic operations, TTL, MergeTree