Hybrid Databases

  • Do you see your data set growing to larger numbers?
    If you have a product offering that serves a niche you feel has amazing potential, setting up a hybrid database from inception can reduce the number of headaches that would arise from a newfound spike in traffic or complexity of the transactions being performed. If you feel that your database will grow at a slower, more organic rate, you may never need to employ hybrid database architecture. Strong consideration should be given to the hybrid options, if you feel that there will be upward momentum at a fast pace.
  • Will the database interactions be highly transactional or minimalistic?
    This is an important question to consider because a singular transaction will take up a much smaller amount of space than a query that has several components. It’s far easier to maintain a database with one million users that only complete a single query, than it would be for those same million users to execute transactions that have multiple components. The space required for complex transactions is far greater than that for a one-and-done use.
  • Is your current database slow or clunky?
    Usually, if this persists for more than a few weeks, procrastination has set in and your employees are numb to the fact that they’re just going to have to wait for the pinwheel of doom to finish processing their tasks. When the database begins to get slower, it’s only a matter of time before it has to be upgraded or replaced altogether. By switching things up to a hybrid database, your employees will be able to experience the best of both worlds, as far as databases are concerned. The SQL side of the equation allows for transactional queries and the NoSQL side allows for CRUD Operations (Create, Read, Update, Delete).

Several aspects of the hybrid database make it popular with the SaaS crowd. One reason is that they increase the application performance, especially when it comes to the read/write operations. Another advantage lies in the fact that the database allows for data distribution across lower cost clusters, all while maintaining ACID properties across more sensitive portions of the dataset. Increased reporting ability across large datasets is also another feature that increases productivity and keeps the project on track.