![]() It does this at the cost of query performance over very large data sets - without indexes it brute forces via mapreduce, which means you really want to specific where to look (which log streams) and when to look (a time window) and in that it excels.ĬlickHouse sweet spot is the indexes are very explicitly configured by engineers who know what the data looks like and how they want to query it. Loki sweet spot is that it has very few indexes, so ingestion is cheap and extremely capable for huge data volumes. But it does this at the cost of ingest as it's doing the work to build indexes during ingestion and so ingest is more CPU intensive and can hit limits here. (+ add comparison on more features)Īll three tools have been providing a decent dashboard experience and we are extremely thankful for their developers for creating a much needed open source BI visualization tool.And what it depends on are your data volume, how you want to query, whether you value ingestion greater than query speed and timeliness and so forth.Įlastic sweet spot is that it indexes everything, and you can query fast as a result. This article is still in progress and we will update this article as these tool make progress. If you have a particular technology talent in-house, then this also can be a plus point in deciding the right tool for your organization. Redash and SuperSet are developed in Python while Metabase is developed in Clojure. Superset vs Redash vs Metabase - Extending platformīeing open source, one can easily extend these tools if one need to. AlertsĬurrently only Redash supports alerts based on certain parameter crossing a particular threshold. Scheduled Emails with summary reports and Alerts are another very useful feature of Data dashboards. dataset Superset vs Redash vs Metabase - Support for Scheduled Emails and Alerts ![]() Roles can be made quite intricate to who can access individual features and which. Gamma users can be assigned multiple roles each controlling access to particular data and queries. Superset supports concept of Admins and Gamma users. A user can be a member of multiple groups. If not sufficient, existing data need to be split between tables to ensure different access level.īoth Redash and Metabase supports concept of users and groups and then allow one to control what level of database and SQL access those groups should have. Though it is typically sufficient for most practical use cases. Please note that in all three data access granularity is primarily based on database table level and can't be go beyond that. This allows organization to restrict data access based on different user roles. Superset vs Redash vs Metabase - Authorization / Access control supportĪll three tools supports a decent permission (authorization) model to allow group of users access to particular data and queries. So if you need to integrate with your in-house ldap or database based authentication backend, currently the only solution is SuperSet. Superset vs Redash vs Metabase - Authentication supportĬurrently Superset supports much richer authentication backend compared to Redash and Metabase who only support Google Oauth for authentication and single sign on. Only few support big data processing backend like Presto, Hive, SparkSQL, Google BigQuery, Elasticsearch currently, but soon all three of them should have support for all these popular backends. Superset vs Redash vs Metabase - Data Backend SupportĪll three tools now support all major sql backends used for data analytics workloads - e.g., Amazon redshift, Postgres, MySql, SQL Server, MongoDB and Oracle. We evaluate these 3 open source BI tools (dashboards) on 4 broader features - 1) Data backend support, 2) Authentication / Authorization support, 3) Support for Scheduled reports by email and Alerts, 4) extension support. Please note that lot of startups have already been successfully using these 3 dashboards :) Here is a quick comparison of Superset vs Redash vs Metabase. It is still early days for these open source dashboards, but they provide a very attractive proposition for internal dashboards already. Earlier this space has been populated primarily by paid BI (Business intelligence) tools like Tableau, Micro Strategy etc, but lately lot of open source alternative are arising with noticeable ones of Redash, Superset and Metabase (Another notable tool is Kibana, but its backend support is limited to Elasticsearch and hence not a general purpose BI tool) Superset vs Redash vs Metabase - Selecting Right Open Source BI Visualization Dashboardĭata visualization dashboards (aka BI tools) are an essential piece for the success of every data analytics project - whether it is using big data technologies or traditional data warehousing approach.
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