Unique challenges exist while developing modern applications in today’s world. While doing so, the first thing comes to your mind is the selection of the database.
These days, there are no data warehouses or single genre applications. Plus, many of them need to interact sporadically with external services like microservices or functions. Given this, modern applications are the lot more complex than the traditional ones due to their hybrid functionalities.
Relational databases are the perfect fit for the static applications. By static means applications that don’t need many changes over the time or don’t require anything more than basic functionalities like reading and write operations. However, these legacy databases cannot equip modern applications.
High availability which drives high-velocity and high-volume data workloads, just look around and think about smartphones, laptops, connected devices, sensors. To thrive with all these functionalities, modern applications require a specific set of data management.
With the growing numbers of connected applications and devices, businesses are turning to multiple solutions built to ingest and serve data in real-time. And hence, RDBMS are coming off as not sufficient. This has necessitated the market to come up with databases that suit the requirements of modern applications.
Problems with RDBMS
Despite the advancement computing through faster processors and high-speed networks, applications with relational databases are becoming slower and stagnant. This is happening due to the change in velocity and volume of the data and their interconnectedness.
This isn’t the only problem. Here are few more of them:
- A large Number of JOINs
When we utilize queries in the databases that have many different tables, there is going to be an outburst of complexities. As a result, more load on computing resources which leads to the corresponding increase in latency.
- Rigid Model
We live in a time when business agility and time to market is at a premium pedestal, hence, requests for changes are going to be often. But this is easier said than done due to the fact that neither schema of relational databases isn’t flexible nor is it designed for frequent changes.
- Higher Response Time
In my experience, in spite of using every possible tactic to iterate and speed up the response time, the results were still saddening. Some of the SQL queries were not fast enough to support our application’s robustness. More to that, denormalizing our data models could impact the performance negatively.
The Definition of Modern Databases
The definition of the modern database is quite subjective, however, there are three basic prerequisites. Relational databases might be able to meet these prerequisites at a certain point and scale but not every time and for every case.
- Infinite Scalability
With the growing sphere of data volume and velocity, the database must also grow. It must scale horizontally and vertically both without having to amend much in hardware. Nevertheless, one basic thing which is to be considered here is its ability to serve your customers satisfactorily.
- Infinite Adaptability
With the never-ending growth of businesses, the database should also grow and keep up the pace with it. What this means is that you should be easily able to mine and extract new data types from your database, as per the requirements, without having much to change or breaking your budget. Your database schema should be flexible to meet your application’s requirements.
- Infinite Exploitability
Storing information isn’t just enough. Exploiting that data is equally important for modern applications. In the age of Big Data, your database must be able to answer questions that you ask in the form of rich queries, aggregation and indexing across multi-layered datasets which are being updated in the real time.
Databases for Modern Applications
Organisation’s searching for a database to tackle Gartner’s three V’s of Big Data – Volume, Velocity & Variety, won’t find the immediate answer to their question.
There are two types of databases which can be called as databases for modern applications. Both of these are much more helpful than traditional databases. Not only they meet the prerequisites but are also good at storing various types of data and sources, which includes geospatial, mobile, IoT, social, etc.
Not only that, the hallmark of modern databases is their ability to provide organisations to do useful things than just storing data.
#1. Non-relational Databases: There are many non-relational databases such as Cassandra, MongoDB, CouchDB, Neo4j and Riak to name a few. All these fit into this category due to their following distinguishing qualities:
- Schemaless
In a relational database, the database schema is the description of the data structure and data which is stored. While in the non-relational database, there is no fixed schema. Without any fixed structure, you can store your data in any manner you want.
- Non-relational
Relations in the database gives the definition of how one database is connected to other. With the non-relational database, this is stored as a single aggregated document which makes complex query processing fast facilitates for infinite scalability.
- Highly Distributable
With the advent of big data, it isn’t sufficient for organisations to store and process data from single device or location. With non-relational databases, multiple clusters of servers can be used to maintain a single large database.
#2. Serverless Databases: In the landscape of serverless technologies, the serverless database is the latest promising technology. The key providers are AWS Aurora Serverless, FaunaDB, Google Firebase Realtime DB and Azure CosmosDB. Some of the outstanding features which makes it worth mentioning here are as follows:
Note: If you’re new to Serverless Database, check out this post for the detailed explanation.
- Scalability
Serverless Databases start-up and shut-down as per the application’s need which makes it infinitely scalable. All this is automated which guarantees that your functions have consistent access to the database.
- Pricing
Serverless Databases are priced on two factors: data storage and data processing on per hour basis. This means that when your database is not processing any data, you’ll be charged only for the data storage (which is fairly cheap). This makes it a perfect solution for applications with infrequent and dispersed traffic.
- Real-time access
With serverless databases, you have access to your database at a granular level. This means, the database gets indexed immediately and those indexes are available instantly. This facilitates the real-time access which is the basic requirement of modern applications.
Conclusion
We can’t outcast our traditional databases right away! However, we can definitely start our transition into a one. The emerging technologies in the database world are looking promising and it’d be interesting to witness what the future beholds!