Directly related to your question:
Both victoria metrics and questdb are compatible (ingestion-wise) with the InfluxDB Line protocol, so migration would be smoother than with other databases. Just point the old ingestion script to the new server URL, and data will start flowing in.
Taking a broader view, the time series database landscape is split into three categories (sorry for adding complexity!):
1. Observability (metrics from your hardware): Prometheus, and other engines that work well with Prometheus such as Victoria Metrics. I think their language is tightly coupled with PromQL. InfluxDB 1.X and 2.X used to be in this camp and were the market-leading solution for observability before Prometheus came along and got incredible adoption. Chronosphere built with m3db is also a big name in this category.
2. General purpose: TimescaleDB is built on top of Postgres, and is now seen increasingly as a super postgres that can also deal with time series data, amongst other things (now focusing on vectors as well).
3. Specialized: kdb+, QuestDB, some OLAP databases that can also do time series (Clickhouse & Druid), and perhaps InfluxDB 3.0 even though it's not OSS yet. Here the focus is on performance, and the data loads tend to be more significant. Industries and use cases often paired with demanding data loads, such as financial services, often require such specialized databases. Some have their prop language (kdb+ with Q), some are closed source (kdb+), and others are OSS & use SQL (questdb, clickhouse, druid). InfluxDB 3.0 also uses SQL (from DataFusion's query engine) but is not OSS yet.