data-diff
bytebase
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data-diff | bytebase | |
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20 | 36 | |
2,842 | 10,029 | |
3.0% | 5.8% | |
9.4 | 10.0 | |
14 days ago | 4 days ago | |
Python | Go | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
data-diff
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How to Check 2 SQL Tables Are the Same
If the issue happen a lot, there is also: https://github.com/datafold/data-diff
That is a nice tool to do it cross database as well.
I think it's based on checksum method.
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Oops, I wrote yet another SQLAlchemy alternative (looking for contributors!)
First, let me introduce myself. My name is Erez. You may know some of the Python libraries I wrote in the past: Lark, Preql and Data-diff.
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Looking for Unit Testing framework in Database Migration Process
https://github.com/datafold/data-diff might be worth a look
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Ask HN: How do you test SQL?
I did data engineering for 6 years and am building a company to automate SQL validation for dbt users.
First, by “testing SQL pipelines”, I assume you mean testing changes to SQL code as part of the development workflow? (vs. monitoring pipelines in production for failures / anomalies).
If so:
1 – assertions. dbt comes with a solid built-in testing framework [1] for expressing assertions such as “this column should have values in the list [A,B,C]” as well checking referential integrity, uniqueness, nulls, etc. There are more advanced packages on top of dbt tests [2]. The problem with assertion testing in general though is that for a moderately complex data pipeline, it’s infeasible to achieve test coverage that would cover most possible failure scenarios.
2 – data diff: for every change to SQL, know exactly how the code change affects the output data by comparing the data in dev/staging (built off the dev branch code) with the data in production (built off the main branch). We built an open-source tool for that: https://github.com/datafold/data-diff, and we are adding an integration with dbt soon which will make diffing as part of dbt development workflow one command away [2]
We make money by selling a Cloud solution for teams that integrates data diff into Github/Gitlab CI and automatically diffs every pull request to tell you the how a change to SQL affects the target table you changed, downstream tables and dependent BI tools (video demo: [3])
I’ve also written about why reliable change management is so important for data engineering and what are key best practices to implement [4]
[1] https://docs.getdbt.com/docs/build/tests
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Data-diff v0.3: DuckDB, efficient in-database diffing and more
Hi HN:
We at Datafold are excited to announce a new release of data-diff (https://github.com/datafold/data-diff), an open-source tool that efficiently compares tables within or across a wide range of SQL databases. This release includes a lot of new features, improvements and bugfixes.
We released the first version 6 months ago because we believe that diffing data is as fundamental of a capability as diffing code in data engineering workflows. Over the past few months, we have seen data-diff being adopted for a variety of use-cases, such as validating migration and replication of data between databases (diffing source and target) and tracking the effects of code changes on data (diffing staging/dev and production environments).
With this new release data-diff is significantly faster at comparing tables within the same database, especially when there are a lot of differences between the tables. We've also added the ability to materialize the diff results into a database table, in addition to (or instead of) outputting them to stdout. We've added support for DuckDB, and for diffing schemas. Improved support for alphanumerics, and threading, and generally improved the API, the command-line interface, and stability of the tool.
We believe that data-diff is a valuable addition to the open source community, and we are committed to continue growing it and the community around it. We encourage you to try it out and let us know what you think!
You can read more about data-diff on our GitHub page at the following link: https://github.com/datafold/data-diff/
To see the list of changes for the 0.3.0 release, go here: https://github.com/datafold/data-diff/releases/tag/v0.3.0
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data-diff VS cuallee - a user suggested alternative
2 projects | 30 Nov 2022
- Compare identical tables across databases to identify data differences (Oracle 19c)
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How to test Data Ingestion Pipeline
For data mismatches, check out data-diff https://github.com/datafold/data-diff
- Data migration - easier way to compare legacy with new environment?
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Show HN: Open-source infra for building embedded data pipelines
Looks useful! Do you have a way to validate that the data was copied correctly and entirely? If not, you might want to consider integrating data-diff for that - https://github.com/datafold/data-diff
bytebase
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Ask HN: What tool(s) do you use to code review and deploy SQL scripts?
We have been building https://github.com/bytebase/bytebase for 3+ years. You can think it of as GitHub/GitLab for SQL changes, with integrated GitOps, code review and deployment.
You can further check out this tutorial to get a feel of our GitOps solution
https://www.bytebase.com/docs/tutorials/database-change-mana...
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Resend – Incident report for February 21st, 2024
We have been working on bytebase (https://github.com/bytebase/bytebase) for 3+ years to address this. With a change review workflow, environment propagations, and try not to disturb the dev flow if possible.
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PostgreSQL Is Enough
Migrations. All my database logic lives in version control.
Popular tooling like Phoenix, Hasura, etc have good built in migration stories.
https://www.bytebase.com looks really promising.
Hover, I do struggle with one big issue: changing database logic (views, functions, etc) that has other logic dependent on it. This seems like a solvable problem.
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A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
bytebase.com — Database CI/CD and DevOps. Free under 20 users and ten database instances
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🚛 Deploy Database Schema Migrations with Bytebase
Bytebase offers a powerful GUI for schema migration deployments. This tutorial will show you how to use Bytebase to deploy schema migrations with features like SQL Review, custom approval, time scheduling, and more.
- Bytebase – The Only Database CI/CD Workspace
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Are "Infrastructure as Code" limited to "Infrastructure" only?
Now there are more subdivided practice: * Policy as Code: Sentinel, OPA * Database as Code: bytebase * AppConfiguration as Code: KusionStack, Acorn * ...... (Welcome to add more)
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🐬Top 5 MySQL GUI Clients to Command MySQL⚡️
Bytebase is an open-source Database DevOps and CI/CD tool for teams, designed to centralize the control and secure your organization’s most valuable asset, the database data.
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database changes tracking tools
I use Bytebase to manage database changes for MySQL with GitOps workflow. I can manage my SQL scripts in my GitLab repo, and trigger a database change issue with committing a MR. Then Bytebase will record it after the issue is executed successfully. But I am not sure whether it supports procedures. Refer to https://github.com/bytebase/bytebase to get more details.
- Version control for database used by C# app
What are some alternatives?
datacompy - Pandas and Spark DataFrame comparison for humans and more!
liquibase - Main Liquibase Source
cuallee - Possibly the fastest DataFrame-agnostic quality check library in town.
dbmate - :rocket: A lightweight, framework-agnostic database migration tool.
dbt-unit-testing - This dbt package contains macros to support unit testing that can be (re)used across dbt projects.
migra - Like diff but for PostgreSQL schemas
sqeleton
jaeger-clickhouse - Jaeger ClickHouse storage plugin implementation
great_expectations - Always know what to expect from your data.
sqldef - Idempotent schema management for MySQL, PostgreSQL, and more
soda-core - :zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
alembic - A database migrations tool for SQLAlchemy.