Metabase vs superset code#

It can pretty much scan tens of GBs in seconds. Athena is a distributed query service and its done wonders for us when it comes to querying our data lake.

We are heavy users of AWS Athena here at Vortexa. Superset > Metabase > Redash Data sources No extra work is needed for the alert and schedulers as those are spun by default, however, you again end up with a bunch of worker pods. Dependencies are redis and a database that are also spinnable through the chart. Redash: No official helm chart, however, the community one is part of the main redash repo, hence closely evolves with redash itself. It ends up with a bunch of pods, some of which workers other for scheduling. Dependencies are redis and a database, and it does provide you with an option to spin those up for you. things like Alerts, Reports and extra data source connectors. The chart itself is pretty configurable and a lot of the functionality is driven within the setup here. Superset: Comes with official support for helm. It then spins up one pod in your cluster and configuration is pretty straightforward and can be done within the tool UI once. As a dependency Metabase requires only a DB connection that it uses for storing state. Metabase: The official Helm chart Metabase comes with has been sadly discontinued, so we’ve had to use a community one. With some of the tools we’ve had to redeploy them a bunch of times until a successful ordered birth happens.

Having a good, configurable and up to date helm chart played a big role in this category.Īnother important criteria here for us has been how easy is it is to debug problems and track failures, and things like multiple kube pods can make things harder. As such, we’ve been using Helm to assist with our Kubernetes deployments.

Metabase vs superset code#

Infrastructure as code has been really important for us at Vortexa. In any case, lets jump right into the details. These tools evolve and change pretty quickly, so other pains we’ve had might not exist by the time you read this. Some of the criteria is biased towards our own deployment methods and stack needs(Kubernetes, AWS Athena etc.), so they might not apply to your case. We’ll now look at the more detailed analysis, which I need to preface with the obvious warnings.