Open source seems a way to go
RedisGears allows developers to write and run functions to implement data flows. this ability enables efficient data processing.
With RedisGears you can:
-Program everything you want
-Implement functions in all environments
-Run the engine where our data resides
-Simplify the architecture and reduce implementation costs.
One of the use cases that I like the most is the operations on multiple models and data structures.
The data processing that RedisGears allows is excellent, efficient and fast, in addition to being able to use multiple Redis models with a very wide programming capacity and very easy to use.
The main components of redisgears:
-GearsCoordinator: it organizes the distributed execution of its functions in each fragment of its database.
-GearsExecuter: schedules and triggers the execution of its functions, which can be triggered ad-hoc, by key space notification or by changes to a sequence.
GearsEngine - The RedisGears runtime runtime environment.
Apart from all this, Redisgears also offers us a very fast and low-level C-API which is integrated through Python for programming.
Something that I find very useful is the python script execution: with the Python source files you can feed the complete scripts, this means that the script can contain normal python functions.
Apart from these Redisgears it is asynchronous, the scripts are executed in a separate thread, so they do not block your Redis instance, this also leads to the understanding that Gears queries cannot be embedded within a Redis transaction. If we have a cluster constantly under memory stress, LUA scripts are the best option to add custom transactional logic to your operations.
RedisGears can be used together with RedisInsight, the two units have the following functions and features:
. List and inspect registered functions.
.Verification for the execution of functions and results.
.Register new functions and verify the new code that is currently running.
The most striking benefit is that you get faster response times when creating your RedisGears scripts.