Bring Git Workflows to Your Data

Commitspark provides tools to put your data under Git version control, enabling non-technical users to take advantage of Git-based data editing workflows that were previously only available to software developers.

AI-Assisted Content Management using Git workflows

Reimagining Data Management Workflows

Create, Review, Publish, Maintain, Retire

Managing data in a team leads to the same workflow challenges that software developers encounter when managing software code. With Commitspark we now made Git - the undisputed champion of software management tools - available for data management by non-technical users.

Open Source Data Editing Front-end

Boost Capabilities of Non-technical Users

Your data editors will love the Commitspark data editing UI that enables them for the first time to work with Git without requiring deep understanding of how the underlying technology actually works.

Simplifies Git
so non-developers can take advantage of Git features.
Git's powerful foundation
remains available behind the scenes for experts and developers.

Branching and Merging

Reduce Conflicts and Errors

With Commitspark, multiple editors can modify data simultaneously on the same project without creating conflicts, reducing stress and need for manual coordination.

Use branches
to keep unrelated data changes apart. This makes it easy for your data editors to work independently.
Use pull requests
to review changes before merging, allowing you to establish sign-off and QA processes that assert data quality.

GitHub, GitLab & Co.

Prevent Vendor Lock-In

Commitspark keeps you in control by connecting to a Git repository and provider of your choice.

Fully Open Source
releases of all our core components ensure you are never locked into Commitspark.
Keep your own Git repository
and simply connect Commitspark to read and write data, letting you remain owner of your data at all times.
Pluggable Git hosting adapters
allow you to connect Commitspark to any Git hosting provider or custom hosting for full vendor independence.

GraphQL + YAML

Get a Boost from Open Standards

Commitspark relies and builds on open standards whenever possible, so much so, that your technical teams most likely already know how to work with Commitspark even if they have never used it before.

GraphQL schema file
serves as a foundation and defines your data model as well as the auto-generated GraphQL API structure.
YAML files for data
make it possible to use Git for storing any structured data you may have while keeping it in a human-readable format at all times.

Git Technology

Speed Up Your Applications

With Git's ability to track data changes, Commitspark unlocks an extremely powerful caching mechanism that speeds up your applications' access to data. And as your Git repository is already hosted, we don't need to add any extra hosting for Commitspark.

Fast API responses
due to an internal caching logic based on Git's ability to track changes to data through commit hashes.
Hosting is optional
when runing Commitspark's data API, as it can be integrated straight into your NodeJS applications as an NPM library and connect directly to where your Git repository is already hosted.

Tags and Semantic Versioning

Increase Application Stability

Never again accidentally break your applications with bad data: With your data and Commitspark's API definition together in the same Git repository, all strategies your developers use to keep applications running can now be employed to protect your application data.

Guaranteed API stabilty
is reached with Commitspark keeping the structural definition of its data API right alongside your data in Git, allowing you to keep perfect control over API changes.
Versioned releases
through Git tags let you enforce that only approved and compatible data reaches production.

CI/CD Pipelines

Automate Reviews

With Commitspark, your developers can easily build automated data validation pipelines that enforce your own business rules. This enables data editors to fix mistakes before they reach production, such as issues that are hard to spot manually.

Automated reviews
are key to ensuring the consistency and accuracy of data before it is published.
Prevent errors
from hitting production with automated tests that prevent editors from merging into production when issues are found.

Git Commits

Assert Data Integrity and Auditability

Commitspark is built on Git which was designed from the ground up to securely track all changes to data in a chain of commits, i.e. records that prove exactly who did what at any point in time.

Cryptographically secure
chains of data changes (commits) allow providing proof of exactly which data existed at any point in time.
Transaction safety
is established automatically by Commitspark by only accepting data changes that attach seamlessly and fully to a previous commit.
Referential integrity
in Commitspark ensures that a reference from one data entry to another is always valid for as long as the reference exists.

LLM Integration

Generate and Transform Text with AI

With Commitspark built entirely on industry standards, AI language models are able to "understand" your data models and generate new or transform existing data.

AI-assisted data creation
lets your editors easily generate anything from single lines of text to entire complex nested components.
AI-powered data transformation
can rewrite or expand existing content automatically, for example, to perform multi-language localization.
AI safety
can be easily realized by preparing AI-based changes in separate Git branches that do not affect production.

GraphQL type safety

Increase Developer Productivity

In contrast to REST data APIs, Commitspark's use of standards-compliant GraphQL allows developers to easily generate type-safe data structures for use in their applications.

Type safety
comes out of the box with Commitspark as a result of using GraphQL, saving developers time from writing boilerplate type validation code.
Type generation
based on Commitspark's GraphQL API allows developers to easily generate application components that match exactly the data structures stored in the underlying Git repository.

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