split roadmap vs voda support

docs/posts/roadmap-2024-H1/index.qmd

@@ -2,7 +2,7 @@
 title: "Ibis project 2024 roadmap"
 author: "Cody"
 date: "2024-02-05"
-thumbnail: commits.png
+image: commits.png
 categories:
     - blog
     - roadmap
@@ -11,173 +11,10 @@ categories:
 
 ## Overview
 
-The Ibis project is an [independently governed open-source
-community](https://github.com/ibis-project/governance) that builds the portable
-Python dataframe library. It is primarily backed by [Voltron
-Data](https://voltrondata.com) but has
-[contributors](https://github.com/ibis-project/ibis/graphs/contributors) across
-a range of data companies and institutions.
-
-This is the first public roadmap for the Ibis project. Thus, there's a bit of
-backstory to explain how we got here and setup the context for where we're
-going. Feel free to [skip ahead to the roadmap](#roadmap) if you're already
-familiar with Ibis.
-
-## Background
-
-The Ibis project was started in 2015 by [Wes McKinney](https://wesmckinney.com),
-the creator of pandas, as a pandas-like interface to Apache Impala. It received
-improvements and support over the years, but really took off under the
-stewardship of [Phillip Cloud](https://github.com/cpcloud) and the [current Ibis
-team at Voltron Data](#who-are-the-core-contributors). It now supports 20+
-backends and is improving rapidly. It's never been a
-better time to get involved with Ibis.
-
-You can see the inflection point in the number of commits to the repository in
-early 2022:
-
-![Ibis commits over time](commits.png)
-
-### Who am I?
-
-My name is Cody and I'm employed by Voltron Data to work on Ibis full-time as a
-Technical Product Manager. I am an Ibis committer and have contributed Delta
-Lake table input/output methods, helped moved the documentation over to
-[Quarto](https://quarto.org), and created the [Zulip
-chat](https://ibis-project.zulipchat.com) for the community.
-
-My job is to help the Ibis community grow and thrive. I have a background in ML
-(especially MLOps) and data products. Ibis solves many challenges I've seen in
-the data space and I'm excited to help increase its adoption as a standard
-Python frontend for dozens of data backends to reduce friction in the data
-ecosystem.
-
-### Why does Voltron Data (VoDa) support Ibis?
-
-Why does Voltron Data employ a Technical Product Manager to work on Ibis
-full-time? Why does Voltron Data employ five software engineers to work on Ibis
-full-time? Great questions!
-
-::: {.callout-note}
-To understand Voltron Data -- or if you're generally interested in learning
-about the composable data ecosystem -- check out the [The Composable
-Codex by Voltron Data](https://voltrondata.com/codex).
-:::
-
-Voltron Data is a for-profit company building
-[Theseus](https://voltrondata.com/theseus), an accelerator-native query engine
-for the composable data ecosystem. On its own, Theseus is fairly bare bones -- it
-needs storage below it, a frontend above it, and a bunch of other components to
-connect things together. Voltron Data's founders and engineers are very
-experienced with open-source software and pioneers of the composable data
-ecosystem. Voltron Data supports Ibis because it is the Python frontend for
-Theseus and can act as a standard Python dataframe API for **any** backend,
-whether you're querying a CSV file on your laptop, running thousand-node Spark
-jobs on a cluster in the cloud, or doing cutting-edge work on-premise with GPU
-clusters. With Ibis, you can write your experimentation code for your laptop and
-scale up to Theseus (or any other backend) seamlessly.
-
-::: {.callout-note collapse="true" title="Why not the pandas API?"}
-This is a great, and natural, question -- if Voltron Data wants a standard
-Python dataframe API, why not just use pandas? The reason is relatively simple:
-the pandas API inherently does not scale. This is largely due to the expectation
-of ordered results and the index. pandas is implemented for single-threaded
-execution and has a lot of baggage when it comes to distributed execution. While
-projects like Modin and pandas on Spark (formerly Koalas) attempt to scale the
-pandas API, any project that attempts the feat is doomed to a dubious support
-matrix of operations.
-
-Instead, Wes McKinney envisioned Ibis as a portable Python dataframe where the
-API is decoupled from the execution engine. Ibis code scales to the backend it
-is connected to. Any other Python dataframe library locks you into its execution
-engine. While they may claim to be easy to migrate to, this is rarely the case.
-The founders of Voltron Data experienced these pains with the pandas API
-themselves in previous efforts, including cuDF. For Theseus and as an
-open-source standard, we believe Ibis is the right approach.
-
-Instead of using Snowpark Python for Snowflake, you can use Ibis on Snowflake.
-Instead of using PySpark or pandas on Spark, you can use Ibis on Spark. Instead
-of using the pandas API on BigQuery (built on top of Ibis), you can use Ibis on
-BigQuery. Instead of using PyStarburst on Starburst Galaxy, you can use Ibis on
-Starburst Galaxy. Instead of using the Polars Python on the Polars execution
-engine, you can use Ibis on Polars. Instead of using DataFusion Python on
-DataFusion execution engine, you can use Ibis on DataFusion. Instead of
-executing SQL strings on DuckDB through the Python client, you can use Ibis on
-DuckDB. And so on...
-
-Ibis brings a Python dataframe interface to data platforms that only have SQL,
-and brings a standard Python dataframe interface to data platforms that have
-their own Python dataframe interface. It is the only portable Python dataframe
-that can serve as a standard across the data ecosystem.
-:::
-
-Voltron Data supports Ibis for the same reason it supports Apache Arrow.
-Open-source standards make it easier to build the composable data ecosystem and
-reduce friction for data teams looking to swap out components as their needs
-change. If you're already using Ibis as your frontend, Apache Arrow for data
-interchange, and Substrait for intermediary representation, you can swap in
-Theseus with ease!
-
-::: {.callout-important}
-[Ibis is independently governed](https://github.com/ibis-project/governance) and
-not owned by Voltron Data. While currently four out of five members of the
-steering committee are employed by Voltron Data (the fifth being at Alphabet
-working on Google BigQuery), we expect this to change over time as more
-organizations join the project. **Ibis will never be solely available for VoDa
-products.**
-
-Voltron Data also welcomes this dilution of power and influence! A healthy
-open-source project is one that is not controlled by a single entity. This is
-true of [Apache Arrow](https://arrow.apache.org) and other open-source projects
-that Voltron Data employees have been instrumental in building.
-:::
-
-### Who are the core contributors?
-
-The core contributors working full-time on Ibis are employed at Voltron Data,
-with deep experience on successful open-source projects including pandas,
-Apache Arrow, Dask, and more. Everything in the Ibis project is made possible by
-their hard work! They are:
-
-- [**Gil Forsyth**](https://github.com/gforsyth): long-time Ibis contributor and
- primary maintainer of the `ibis-substrait` package
-- [**Jim Crist-Harif**](https://github.com/jcrist): the engineering manager for
- the Ibis team at VoDa
-- [**Krisztián Szűcs**](https://github.com/kszucs): long-time Ibis contributor
- and primary author of the precursor to [the big refactor](#the-big-refactor)
-- [**Naty Clementi**](https://github.com/ncclementi): newest member of the Ibis
- team at VoDa recently focusing on [geospatial support in
- DuckDB](#geospatial-improvements)
-- [**Phillip Cloud**](https://github.com/cpcloud): the tech lead for the Ibis
- team at VoDa
-
-If you're interacting with us on GitHub or Zulip, you'll definitely run into at
-least one of them! They make the Ibis project the delightful software it is
-today and are always happy to help.
-
-### Who else supports Ibis?
-
-Anybody who contributes to Ibis is a supporter of Ibis! You can contribute by
-[opening an issue](https://github.com/ibis-project/ibis/issues), [submitting a
-pull request](https://github.com/ibis-project/ibis/pulls), [using Ibis in your
-project](https://github.com/ibis-project/ibis/network/dependents), or [joining
-the Zulip chat](https://ibis-project.zulipchat.com) to discuss problems or
-ideas.
-
-Notable organizations that support Ibis include:
-
-- [**Claypot AI**](https://www.claypot.ai/): contributing the Apache Flink
- backend
-- [**Exasol**](https://www.exasol.com/): contributing the Exasol backend
-- [**Google's BigQuery
- DataFrames**](https://github.com/googleapis/python-bigquery-dataframes): a
- pandas API for BigQuery built on top of Ibis
-- [**RisingWave**](https://risingwave.com/): contributing the RisingWave backend
-- [**Starburst
- Galaxy**](https://www.starburst.io/blog/introducing-python-dataframes/):
- supporting Ibis alongside their native PyStarburst dataframes
-- [**SuperDuperDB**](https://github.com/SuperDuperDB/superduperdb): bringing AI
- to any database Ibis supports
+Welcome to the first public roadmap for the Ibis project! If you aren't familiar
+with the background of Ibis or who supports it nowadays, we recommend reading
+[why Voltron Data supports Ibis](../why-voda-supports-ibis/index.qmd) before the
+roadmap below.
 
 ## 2024 roadmap
 
@@ -200,9 +37,10 @@ disorganization as we get it up and running efficiently. In general, we have:
 - **Label-specific views**: consisting of issues for specific labels, like
  documentation or a large refactor
 
-Right now, the team at Voltron Data sets the roadmap and priorities. Over time
-as more contributors and organizations join the project, we expect this process
-to diversify and become more community-driven.
+Right now, [the team at Voltron Data](../why-voda-supports-ibis/index.qmd) sets
+the roadmap and priorities. Over time as more contributors and organizations
+join the project, we expect this process to diversify and become more
+community-driven.
 
 ### Overall themes