Hence, using a caching engine like Redis along with your database is a good idea if the number of requests processed is huge.

Web Dev One table that has a column with the user ID (we called OrganisationID) and the counter, and a second table called storage, which contains some random data, such as a record ID, timestamp and the index of what we're inserting.Thinking of this, we thought about the idea of using Redis to store the counter for the user and then the only database work that is required is the storage of the processed data, and updatingthe final request count when the user session expires.Below is MySQL version of the PHP script:From this test, I think that means that we'll most likely be using redis for this part of our service, and possibly other areas as well.As you can see from the graphs above, using Redis to store and query the quota for each HTTP request, instead of doing it in the DB is a lot quicker, in fact, on average, over the 5 runs of each script that we did we saw a 51.4% reduction in both the whole process to complete and the time to store each record into the DB.CritiMon - Critical Monitoring arriving Q1 2019Redis is not a replacement for a MySQL database, although Redis does support data persistence its not really designed as a proper database and kind of work together side by side with a normal more convential style database.We are execited to announce we have developed a new MySQL connector library to allow you to connect directly to your MySQL databases directly if required from your Android apps.Redis is an open source in memory data structure used as a database, cache and message broker. {{ parent.articleDate | date:'MMM. {{ articles[0].isLimited ? It supports the storage of various different data types, and from our understanding, its primarily used as a way of caching content that can be retrieved later quickly and efficiently, therefore offloading some of the workload of your database servers such as MySQL. Lets forget about the initialisation side of things, as that's not where the issue is, but from the data processing side, its doing a lot of DB work. If it is not present on Redis, we would search for that key on our MySQL database and store that key to Redis. You can find more information about Redis by Before we get into our little experiment, lets first of all give some brief details about what Redis is.Don't worry about the DBHelper and DateTimeManager classes, they are just internal class function we use as helper methods for things we need on a regular basis in our internal web librarySo the process using Redis would be as follows, again excluding the initialisation, at the initialisation stage, we would create a redis key which would be some sort of identifier for the user.As you can see above, the number of steps is exactly the same, but instead of querying the DB and updating the quota in the DB for every request, we query Redis instead and only update the quota in the DB when the session expires using the counter from redis.The basic idea of both is to check the quota value, if below the threshold (we selected 5000) insert a record to the DB, increment the counter and then exit and show the time it takes for the whole process to run, and the average time it takes to the storage (the storage including the quota check, storing a record, and increment the quota).We're currently working on a project, don't want to give too much details yet, but it is something we plan on releasing in the not too distant future as an early access preview, but it consists of multiple different components.

The idea of the service, is a user initialises using their API key by sending us an initialisation request received by the engines REST API, the API key is queried in the database, and if successful, an OK response is returned, after which the user can keep sending us POST data, that we receive again through the engines REST API, process and store in the DB. Security