Synchronize

When building applications and dealing with data, we discern two distinct stages in the lifecycle of data: the write and the read path. When using a typical client/server model the client requests data fetches and mutations on demand. In the synchronization paradigm, we turn this model on its head. Instead of requesting the data from the server when needed, we already synchronize the data from the server to the client. This happens during the write path, meaning the data is already available before it’s even requested.

This has a number of tangible benefits:

• Performance is improved. Instead of fetching on-demand and waiting for several hundred milliseconds, the data is already available.
• The development process is simplified, as the developer can focus on the business logic rather than the data synchronization. This in turn reduces the turn-around time for new features.
• Product teams can more easily integrate data from other teams. This increases platform cohesion.

ReJot helps you to merge the write and read paths. By setting up connections between multiple databases, or databases and apps, you get to reap the benefits of synchronization without the hassle of setting up complex integrations. Our synchronization engine is built to scale and help you achieve your goals quickly.

Use Cases

Transform

Transformations are a natural part of any system that handles any amount of data. The way data is structured in your database differs from how it’s exposed via APIs, transmitted through webhooks, or shared with other teams through event streaming. Data is constantly transformed to fit the needs of the system that consumes it. ReJot aims to make transformations a first-class citizen of your data platform.

Control

In enterprise systems, we often think about access control on the level of endpoints. When a client sends a request to an (API) endpoint the server probes some (de)central authority to figure out if the request is allowed. A client in this case can be a user with a certain role, but it could also be a service controlled by a different team.

Since ReJot is a data platform, we think about access control on a different layer. Our access control system does not check what action a user is allowed to do, but rather, which data a system is allowed to see. The system, in turn, is responsible for checking permissions of the user using the service. This gives you a multi-layered access control system when using ReJot, which is more flexible than the traditional approach.

This access control strategy makes it easier to stay compliant with regulations such as the GDPR and CCPA. The teams that work directly with personal data usually have the most intimate knowledge of what data is allowed to be shared. By giving them the ability to control what and how data is shared, you can ensure that you are always compliant. ReJot combines discretionary access control with other forms of access control (typically role-based access control) for maximum flexibility.

Use Cases

Own

It is widely accepted that when teams deliver more value when they have ownership over their code. Autonomous teams are more productive and more innovative. We believe this holds even more so for data. However, this belief is not as widely accepted just yet.

We have seen that enterprises often take shortcuts when it comes to data management. When looking for actionable insights, it is tempting to directly read from a product team’s database to extract aggregations as needed. This comes back to bite the teams involved, as now the data model is implicitly locked without the product team’s consent. Misinterpretations of the data model are also common. Teams expect their data model to be internal, and thus are under-documented. A business analyst interpreting data differently can lead to taking incorrectly informed decisions later on.

At ReJot, we understand that data needs to be made available to whomever can extract value from it very quickly. This is why ReJot makes it trivial define how data should be transformed and published. By keeping the transformation rules next to the data model, we ensure that data can be shared with consent and speed while keeping the ownership with the product team.

Use Cases