4/3/2023 0 Comments Metabase helm chart![]() ![]() Raft takes a special stance on using and contributing to open source solutions that run well on the cloud. Metabase Helm chart How to use git clone :daothaison/metabase-chart.git cd metabase-chart helm install metabase charts/ -f values. In this episode, we dive in to learn how Trino enables Raft to supply government sector clients with a data fabric solution. One particular challenge they face is dealing with fragmented government infrastructure. Raft provides consulting services and is particularly skilled at DevSecOps. In this episode we sit down with engineers, Steve Morgan and Edward Morgan, to discuss how they use Trino at Raft. Demo of the episode: DML operations on Iceberg using Trino: 1:15:31 Pull request of the episode: PR 13111: Scale table writers per task based on throughput: 1:11:37 Concept of the episode: Trino Iceberg connector updates : 1:01:38 Concept of the episode: The Puffin format: 50:53 Concept of the episode: Branching, tagging, and auditing, oh my!: 43:54 Concept of the episode: Metadata catalogs: 35:40 Concept of the episode: Why Iceberg over other formats?: 16:50 Concept of the episode: What is Iceberg?: 11:27 ![]() We'll talk about all of this and more so don't miss it! ![]() So much so that you can use Trino as the sole query engine atop Iceberg to support your data lake. Likewise, we've improved Trino's writing capabilities around Iceberg. Since the first episodes, Iceberg has finalized the v2 spec and added a lot of new features along the way. We also have a new guest, Tabular Developer Advocate Sam Redai, shedding light on this incredible community as well! We also discuss and demo a bunch of new features that have come out in the Trino Iceberg connector. Want to add support for your datastore or data engine? Read more () about the technical requirements.Join us for this next episode of the broadcast, where we bring back Ryan Blue, the creator of Iceberg, to discuss some of the latest happenings in the Iceberg community. **A more comprehensive list of supported databases** along with the configuration instructions can be found (). Here are some of the major database solutions that are supported: Superset can query data from any SQL-speaking datastore or data engine (Presto, Trino, Athena, ()) that has a Python DB-API driver and a SQLAlchemy dialect. You can obtain them in online repositories or the Artifact Hub. Step 1: Find or Create a Helm Chart To install a helm chart, you either have to find it online or create a helm chart yourself. 8 articles Explore this topic Topic Permissions Permissions, groups, data sandboxing, and auditing. The steps for installing an app with Helm include obtaining a helm chart and issuing the helm install command referencing that chart. 8 articles Explore this topic Topic Administration and operation Guidance on running and administering Metabase at scale. A **cloud-native architecture** designed from the ground up for scale Analytics with Metabase Guidance on data analysis, modeling, and making better data-driven decisions. An **API** for programmatic customization Highly extensible **security roles and authentication** options Lightweight, configurable **caching layer** to help ease database load A wide array of **beautiful visualizations** to showcase your data, ranging from simple bar charts to geospatial visualizations Out of the box support for **nearly any SQL** database or data engine A **lightweight semantic layer** for quickly defining custom dimensions and metrics A powerful, web-based **SQL Editor** for advanced querying A **no-code interface** for building charts quickly Superset integrates well with a variety of data sources. Superset can replace or augment proprietary business intelligence tools for many teams. Superset is a modern data exploration and data visualization platform. (RELEASING/README.md#release-notes-for-recent-releases) | A modern, enterprise-ready business intelligence web application. ![]()
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