An Introduction to Serverless Databases Architecture

  • Posted by Sharad Jaiswal

    Understanding the Serverless Architecture

    There is another term looming in the technology forums, just after all the hype about Microservices Architecture is gone. Though this seems to be no new concept but has grabbed all the limelight and this hot topic which is the talk around is "Serverless Architecture and Serverless computing".
    The serverless computing is a cloud computing execution model which means that the cloud provider is managing the distribution of computer resources dynamically. This concept was around for some time with the advent of As A service or BaaS or MBaaS but was at a different scale until AWS Lamba, Azure Functions, and Google Cloud came into the picture with their serverless solutions.
    Serverless computing requires servers and that is where the serverless databases come into frame. All that is required is to just know the right database service to start using the advanced and featured technological solutions of today’s technical era.

    Various Serverless Databases available in the market.

    There are already several well-known databases out there, like Azure Data Lake and many more.

    Below is the list of few more serverless databases available in the market.

    • Amazon Aurora Serverless
      Amazon Aurora Serverless database scales up to the database storage of 64 terabytes and is fully manageable. This serverless database comes with two different editions compatible with both MySQL and PostgreSQL, and it is also compatible with other systems like MariaDB, Oracle and many more.
    • Google Cloud Store
      It is a document-oriented store which offers database component of Google App Engine as a standalone service. The firebase which is also owned by Google is available in two different payment plans to give their customers multiple options to ensure their convenience. These plans include a fixed plan or pay-as-you-go plan. The firebase includes a hierarchical database.
    • FaunaDB
      The FaunaDB is the most significant transactional database which is distributed worldwide and its technology is based on the giant app on the internet, twitter.
    • DynamoDB
      The DynamoDB is an Amazon service and is an entirely managed NoSQL database service. Creating the database tables is easy and straightforward with DynamoDB.Not just creating, the user can also store and retrieve any amount of data, as it is able to serve any level of traffic. The DynamoDB is capable of providing high-speed performance with seamless scalability.
      Also, Read DynamoDB interview questions
    • RavenDB
      RavenDB is yet another second-generation document database which features live projections and multimap, and also the design decisions like making it Safe-By-Default. All these features of RavenDB make sure that it provides a real added value and is not just another NoSQL database solution.
      Also, Read RavenDB interview questions
    • MongoDB 
      MongoDB is a large-scale open source database used by companies of all sizes, across all industries and for a wide range of applications.MongoDB is developed for scalability, high availability, and performance. It provides high scalability for both reads and writes. It’s native replication and automated failover enabled operational flexibility as well as enterprise-grade reliability.
      Also, Read MongoDB interview questions
    • CouchDB
      CouchDB is a database that embraces the servers completely, where the users can store data with JSON documents and access the documents and also query the indexes with their web browser through HTTP. It works well with mobile applications and modern web. Using CouchDB the users can distribute the data or apps efficiently. It also supports master-master setups with automatic conflict detection.
      Also, Read CouchDB interview questions
    • JasDB
      The JasDB is NoSQL database which uses a document-based storage mechanism. It was built with ease of use and minimal configuration in mind in order to provide an alternative to current document-based implementation.JasDB is easy to use and can be installed and configured in no time at all.

    Pros of using a Serverless Databases

    • Lower cost
      Serverless saves, in terms of both human resources and computing power. Gone are the days when you used to spend thousands of dollars on servers. You don’t need to pay to reinvent the wheel for authorization, image processing or to manage the infrastructure. And when there is no need for it always on the servers, the operational costs plummet.
    • Enhanced scalability
      Everyone strives to make their app the next giant app on the internet like Facebook or Twitter, but can the load be handled, if that happens? The provisioning infrastructure is a big risk and so is being unprepared when success strikes.
      You don’t need to make such choices in serverless architecture, just one online training program which is scaled up to 40,000 users in six months without a single server.
    • Improved latency and Geolocation
      The three things on which the apps ability to scale depends are the number of users, the location of those users, and the last one is network latency. Today's advanced apps have global audiences that can create latencies which can diminish. With serverless, the providers have points of presence near every user and the apps perform well for everyone.
      All kind of apps, from photo sharing to data sharing, serverless can accommodate the wide-ranging needs of the application developers. Expect serverless to become a standard approach to offloading functions in order to execute closer to end users and devices when the data continues to grow on the server. With reduced costs, latency, complexity, and time to market, the serverless is poised to become a staple of the app space.

    Cons of using a Serverless Databases

    • Limitations on Performance and resources
      If not used very often the database can suffer from more significant response latency compared to a database which is actively running on a dedicated server, container or in a virtual machine.
      This happens because the cloud provider spins down the serverless database completely if not used frequently, that is if the runtime needs some time to start up then it will create more latency. Serverless computing doesn’t suit some computing workloads like the high-performance computing ones. The providers are the reason behind the resource limits, and another reason is that it would probably be more cost-efficient if bulk-provision is made to the number of servers that a user needs at any given period.
    • Monitoring and Debugging
      Diagnosing resource usage problems or performance with serverless architecture is difficult when compared with traditional server architecture. There are no possible ways to dig in more details about the attaching of debuggers, profilers or APM tools, though complete functions can be timed.
      The serverless architecture runs in a closed source environment that means its performance characteristics are not easy to replicate in a local environment. Luckily, you will find some amazing serverless monitoring tools out there in the market that you can put to use.
    • Security Reasons
      Serverless databases are sometimes misunderstood as more secure than that of the traditional databases. To some extent, it can be considered as a true fact because the operating system’s vulnerabilities are handled by the cloud providers. The numbers of attacks are increasing because there are many more components to the application when compared to traditional architecture and every element is supposed to be an entry to the serverless app.

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