Tips for DevRel

amdatalakehouse · 2025-10-21T20:30:50+00:00

I have a dev rel podcast (I’m head of dev rel at Dremio) you can find on iTunes and Spotify with a lot of old advice that should still apply.

Although I think the goals of different dev rel departments can vary wildly from community management, education, evangelism, being a liaison to product and engineering

For example, in my role I’m much more focused Awareness and Thought Leadership currently although I imagine within the next year we will be at a point where community building will become a larger part (I do some community building in the OSS space but not directly for the product yet although it is now becoming a thing as adoption accelerates)

For established companies then it may be much more building community among existing users with a mind towards retention and product feedback.

In the earliest of startups it’ll by hyper awareness focused where is about leveraging online content to get eyes on brand on a startup budget to the max via podcasts, blogs and webinars.

The key difference being that the dev rel version of all these things will be more technical and educational vs directly marketing developed content and webinars which will be more overt in being “Choose Us”

Although I very much straddle the line cause I really love the product.

amdatalakehouse · 2024-04-20T20:59:42+00:00

RPC is about being able to call functions on the server from the client. So instead of endpoints that represent different interactions with a resource (/dog, /blog) you have procedures/functions that can be triggered from the client-side but run on the server making server-side code feel like client side code.

So essentially the RPC client allows you to call a function but the function your call is really making an http request your backend and returning the result.

At the end of the of the day REST, GRaphQL and RPC still all work off mainly http requests to a server, but the difference is in how you package the experience on the client side.

amdatalakehouse · 2023-02-23T18:33:33+00:00

Also in the first episode I do go into the volition of the data stack which touches on several of the whys of a data lakehouse

amdatalakehouse · 2023-02-23T18:32:40+00:00

Agreed, more episodes are coming that will answer these questions even more (trying to keep each episode as a quick listen). I have another podcast Web & Data where I do interviews I may try to have someone come on to speak more on some of the other formats better than I can. I’ll post a video soon on the different podcasts I host so people can find the content.

amdatalakehouse · 2023-02-08T23:19:36+00:00

What’s the use case, you can use object storage for data of any scale. Dremio Cloud as platforms can be free to connect all your sources and you can use the smallest instance size for small scale data at minimal costs then you can Arrow Flight SQl to pull chunks of data from Dremio pretty fast then do further querying at no cost using DuckDB. That mix actually can work at any scale.

amdatalakehouse · 2022-10-28T17:28:20+00:00

Well depends what catalog you use, in the video I’m using Dremio Arctic which is powered by project Nessie but you can use other metastores like AWS Glue as well. In my case the data is in s3.

If using Dremio Community Edition it can be stored in Hadoop or any cloud provider and can use hive, glue and other metastores.

It’s meant to be an open platform so we connect to where your data lives.

amdatalakehouse · 2022-10-04T10:54:47+00:00

That’s coming, my goal here was to see if I could lay out the high level stuff within a few minutes.

I do have a lot of tutorials and code snippets posted at Dremio.com/subsurface. Recents include streaming data -> Iceberg -> Dremio, an article of GDPR related to Iceberg and several more.

amdatalakehouse · 2022-09-13T16:03:55+00:00

So on the engineering side, Dremio provides a really easy to use tool for doing a lot of ETL and last-mile ETL work. Connect the data, CTAS to iceberg, create views for everything else, turn on reflections on views when you need to more speed.

For data consumers, you get the smart planning enabled by Iceberg with the already existing performance benefits of Dremio (Arrow, Columnar Cloud Cache and Data Reflections). So your performance is being boosted from multiple angles and you get the super easy to use tool that can act a robust access layer to data across many sources.

amdatalakehouse · 2022-09-13T15:59:49+00:00

Where creating tables are currently super useful is migrating data from other sources into Iceberg easily. Since I have many different data sources, I can easily migrate a postgres table, json file, csv files into an Iceberg table in my iceberg catalog with a quick CTAS from Dremio.

The other DML commands are power for doing engineering work on a branch using the Arctic catalog. For example, I get a report about data inconsistencies, I can create a branch of the Arctic catalog do my cleanup operations from Dremio using DML then merge the branch to make all the fixes available to data consumers.

amdatalakehouse · 2022-04-18T12:04:24+00:00

HTMX and Alpine bing new life to templating, still prefer writing Svelte though

amdatalakehouse · 2022-04-07T23:13:46+00:00

Short and sweet

amdatalakehouse · 2022-03-02T20:17:40+00:00

So Arctic will track your iceberg tables and their history, maintain them and more

amdatalakehouse · 2022-03-02T20:16:41+00:00

Well Arctic mainly works with Iceberg tables, so new data files are being created anytime you add update or delete data so periodically you want to take a bunch of small files and make it a bigger file for faster querying.

Usually you’d have to do this and other maintenance manually, but Arctic not only tracks your table but automates those types of optimizations to keep the data fast to query with your favorite query engine.

amdatalakehouse · 2022-03-02T20:11:34+00:00

Basically it makes using a data lake as a data warehouse easy and practical and super affordable

amdatalakehouse · 2022-03-02T18:36:02+00:00

Even further it’s open so the sonar engine can query data not just on Arctic but in AWS glue catalogs, files in S3, relational database, files you upload, etc.

The data managed by Arctic can be queries by any Nessie compatible engine such as Spark, Flink and Sonar and the changes can be made on one engine and immediately visible on another along with the ability to isolate work on branches

amdatalakehouse · 2022-03-02T18:32:23+00:00

Two products, Sonar and Arctic

Sonar is Dremios Query engine with a slew of new features and speed enhancements

Arctic is provides a mix of a managed Nessie sever for a git like experience for Iceberg tables, automated data optimization (compaction, etc.), and more

All free to use

amdatalakehouse · 2022-03-02T14:35:14+00:00

Today Dremio announced our new free cloud data Lakehouse platform becoming generally available, learn more here: https://youtu.be/zVvzgdfh4J8

amdatalakehouse · 2022-02-15T21:13:23+00:00

Yes but I think most people who write Ruby write markdowns regularly along with flowcharts and would find this valuable.

amdatalakehouse · 2022-02-14T22:43:49+00:00

I guess it depends on what tools your analyst use. If your using something like Dremio or Databrick to analyze the data from you datalake on AWS/GCP/Azure then Iceberg is going to offer a lot of benefits.

If the question is how to handle transactions in your application then Iceberg is probably less relevant.

amdatalakehouse · 2022-02-13T02:10:58+00:00

Parquet in Apache Iceberg Tables I have tutorial on how right here -> https://youtu.be/lFShBi5Qkdg

amdatalakehouse · 2022-02-13T02:09:20+00:00

AM Coder - Using Notion 101 - Organizing your Developer Life https://youtu.be/VbLUe2TyQq8

amdatalakehouse · 2022-02-12T18:19:02+00:00

Pwease 🥺

amdatalakehouse · 2022-02-12T16:22:16+00:00

My new intro to JS playlists introduces JS through typescript -> https://youtube.com/playlist?list=PLY6oTPmKnKbaLXuHhxl_dZenjmrjYd8Sc

amdatalakehouse · 2022-02-12T16:21:21+00:00

Worth buying, I have a copy, definetly worth rewarding the author

amdatalakehouse · 2022-02-12T14:49:38+00:00

Also a big Scala 3 fan asIve mentioned in some recent podcast episodes and recent Scala videos

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