dbt-tidb
ibis
dbt-tidb | ibis | |
---|---|---|
2 | 23 | |
14 | 4,271 | |
- | 7.1% | |
4.7 | 10.0 | |
5 months ago | 1 day ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dbt-tidb
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Data Transformation on TiDB Made Easier
Data build tool (dbt) is a popular open-source data transformation tool that enables analytics engineers to transform data in their warehouses through SQL statements. The TiDB community recently released the dbt-tidb adapter to make TiDB, a distributed SQL database to work with dbt. Through the dbt-tidb plug-in, analytics engineers working with TiDB can directly create forms and match data through SQL without having to think about the process of creating tables or views. They can also use Jinja, a dbt template language for writing SQL, test, package management, and other functions, which greatly improves efficiency.
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Upgrade dbt adapter to support new dbt-core
Recently, we published a new release of dbt-tidb, an adapter that enables dbt to work with TiDB.
ibis
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Show HN: Hashquery, a Python library for defining reusable analysis
I really don't understand the appeal of dbt vs a proper programming language. The templating approach leads to massive spaghetti. I look forward to trying out something like Ibis [0]
0: https://ibis-project.org/
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This Week In Python
ibis – portable Python dataframe library
- Ibis: The portable Python dataframe library
- FLaNK Stack 26 February 2024
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Quarto
The main benefit is that you get a Python (or R, Julia or Rust) interpreter. So you can evaluate code. A good example of the value of this is the Ibis docs which use Quarto: https://ibis-project.org/
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Polars – A bird's eye view of Polars
Ive found polars quite intuitive, though for python, I lean more towards [ibis](https://ibis-project.org/). The interface is nearly identical, but ibis has the benefit if building sql queries before pulling any actual data (like dbplyr) — whereas polars requires the data to be in-memory (at least for rdb’s, though correct me if Im wrong)
this to me seems like a good argument for only using ibis, but Im happy to be convinced otherwise
- Ibis – Universal Interface for Data Wrangling
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Vanna.ai: Chat with your SQL database
Please add Ibis Birdbrain https://ibis-project.github.io/ibis-birdbrain/ to the list. Birdbrain is an AI-powered data bot, built on Ibis and Marvin, supporting more than 18 database backends.
See https://github.com/ibis-project/ibis and https://ibis-project.org for more details.
- Ibis
What are some alternatives?
pydwt - Modeling tool like DBT to use SQL Alchemy core with a DataFrame interface like
snowflake-connector-python - Snowflake Connector for Python
dbd - dbd is a database prototyping tool that enables data analysts and engineers to quickly load and transform data in SQL databases.
PySpark-Boilerplate - A boilerplate for writing PySpark Jobs
semver - Semantic Versioning Specification
Apache Impala - Apache Impala
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
pangres - SQL upsert using pandas DataFrames for PostgreSQL, SQlite and MySQL with extra features
data-diff - Compare tables within or across databases
sqlite_scanner - DuckDB extension to read and write to SQLite databases
katacoda
nodejs-polars - nodejs front-end of polars