Pick upa BI toolJust want a standaloneSQL-based analyse AppMetabaseIframe embeddingMetabase,Redash,Grafana,supersetSecondary custumizationRedash,Grafana,superset,MetabaseLog analyseGrafana,Redash,superset,MetabaseMore requirement?Buy enterprise/SaaS version of them
In our scenario (Backend stack), the following is the main reason for Redash
No source code modification required.
Raw SQL support (but with injection, no sql pre-compile), which is easier to intergrade with format agnostic computational databases.
Query definitions && low code visualization support
Redash use a asynchronous connection to fetch and cache results.
Scalability & High availability
Liebig’s law of redash
python-rq uses Redis as a queue implementation, but lacks cluster support. So the redis instance requires AOF/RDB setup.
Session/authorization: require shared sessions for multiple Flask apps(redis/db/traefik).
Scheduler: only single instance per Redis.
Production
For production use, you must deploy redash instances behinds a ELB.
However, there are no OSS HA solution available, buying a SaaS version may be a better way for less maintance and also a way to contribute for open source.
One more thing
Redash use Jinja as its template engine, NO sql injection protection is provided.
Redash front is NOT a low code solution, we have verified the productivity of redash with Echart.js +vue, it showed that it’s faster to write js manually than edit json layout in redash.