The flexibility of the NoSQL data model

Unlike traditional databases, MongoDB can gather data without a predefined structure and adapt its dynamic scheme as needed. The tabular schema is no longer used, as regards NoSQL databases, the logical representation of a NoSQL database resembles a tree structure. MongoDB is a document-oriented database management system that organises data in JSON documents and collections. These documents contain pairs of values or keys of different types, including nested documents and arrays. The structure of key/value pairs can vary across different documents. Additionally, MongoDB also allows for the use of GridFS, which enables it to function as a file system using the JavaScript query language.

Advantages – based on use cases

MongoDB and MySQL both have their various strengths and benefits, which include indexing, query language (both rely on natural language and offer a graphical interface when needed), security (each offers authentication, access control and data encryption), and compatibility with various programming languages (Java, Python, Node.js, server-side PHP, Ruby and C#). Scalability and strong read-write performance set MongoDB apart in multiple use cases.

MySQL only allows for vertical scaling, i.e., you can only add resources to the database server (RAM, CPU) for scalability. During the replication process, read-only copies are created on other machines, which may result in delays in updates and the user’s access to information.

MongoDB goes even further by incorporating both vertical and horizontal scaling into its design. Two mechanisms, clustering and sharding, are used to achieve this. Clustering, which involves groups of MongoDB servers with identical data (three servers minimum), and sharding, which spreads different parts of the data across multiple servers for load distribution, high availability, and security in case of hardware failure.

MongoDB stands out from the rest in terms of performance, particularly in writing, when using the “insertMany()” API command to insert or update numerous records. When dealing with a high volume of records, MySQL is the faster option.

So, your project, available hardware, and the type of data you work with (structured, semi-structured or unstructured) will determine the most suitable technology.

Of course, there are alternatives or plugins to address the limitations of MySQL or make up for missing features – depending on the use case. For instance, with an RDBMS like MariaDB, you can enable multi-master clustering using this approach. However, attempting to adapt a technology to needs it wasn’t designed for in the first place will inevitably make maintenance complex, increase the risk of malfunctions, and lower performance.

On the other hand, if MongoDB proves to be more suitable, we can’t overlook the skills needed to deploy, configure and maintain MongoDB’s architecture, as well as understand replicate set and sharding ^[1] (Find out more about the differences between the two). If you need it, choosing an OVHcloud-managed solution like Managed Databases for MongoDB could be the ideal option. 

Why choose MongoDB over any other non-relational database management system?

There are many other document-oriented databases out there, including Couchbase, CouchDB, Oracle NoSQL Database, Amazon DocumentDB, Azure Cosmos DB, and more. Nonetheless, MongoDB is notable for its versatility, performance, scalability, and features. This makes it a popular DBMS for various use cases, including e-commerce catalogues, web/mobile apps with user-specific content customisation (e.g., social media), payment systems, serverless design, workload migration, content management, gaming, IoT data collection, and much more. It spans use cases involving big data and artificial intelligence.

Unlock MongoDB’s full potential effortlessly with OVHcloud

Installing MongoDB on a single server, VPS or Public Cloud instance is straightforward. However, things might get more complex when the project enters production and/or gains momentum, or requires a stable environment and deployment of a multi-node cluster. This also includes mobilising specialised resources that could be allocated to your main business, like developing applications. This particularly holds true for use cases that demand solid compliance, such as health data hosting and management.

OVHcloud offers a managed MongoDB solution — i.e., it is managed for you by our team and hosted in a sovereign cloud. — designed and delivered in partnership with MongoDB’s teams. Since our Database as a Service (DBaaS) is not shared, it allows you to free up your SysAdmins without compromising performance and compliance. Each user has their own environment, except for the Free Tier Discovery offer, where CPU and RAM resources are shared. This service also helps you tackle the challenge of scaling your database, syncing and distributing data across several nodes, as well as backing it up (included in our plans).

Find out why you should choose MongoDB managed on OVHcloud, an expert in MongoDB infrastructure – including deployment and administration. You can achieve greater efficiency and build more reliable, powerful and secure applications, while optimising the total cost of ownership (TCO) of your data.

Want to go further ?

At first glance, the idea might seem absurd: migrating to NoSQL, a non-relational database management system, while using a MySQL or Oracle database. It’s like putting petrol in a diesel car. Of course, the code will need be altered, but it is certainly doable. Read the MongoDB webinar “Migrating relational database workloads to the MongoDB Document Model”

^[1] Soon, the OVHcloud Managed Databases for MongoDB service will include the sharding set-up feature. This has been added to our roadmap.

Aiven powers OVHcloud’s growing DBaaS portfolio, Managed Cloud Databases. Read this blog post from Aiven CTO, Heikki Nousiainen, to find out how their customers have achieved better agility and efficiency in the cloud – and how you can do the same!

Why business agility is important

For companies in today’s changing world, it’s crucial to remain agile and adapt to changing circumstances. Failure to change directions, sometimes in mid-step, can result in needless expense and hurt a company’s image. 

When we talk about agility, we often think of product and corporate strategy and other long-term progressive endeavors. That’s valid, since both the product roadmap and the overall strategy of the company must be able to change to fit the market environment, as well as in response to internal developments.

But agility is also relevant in operations and infrastructure, where a company’s internal workings must also be able to accommodate change. New innovations come to market every day that can save money in your operating expenses; and every now and then tools become obsolete, even though you’re still using them. If a company doesn’t react in a timely manner, these changes can result in reduced efficiency or actual loss of business.

What’s more, any company’s operations and infrastructure absolutely must support innovation on a fast cycle, or compromise their ability to adjust to change.

DBaaS in the cloud makes sense

One of the pieces of infrastructure that it most makes sense to purchase as a service is databases and related services. Setting up and managing a database is a specialized skill, especially doing it well, and requires resources that can instead go into developing a company’s own products. In practice that means that instead of hiring a database admin, you can hire a developer for your product team, while another company with its own skilled team is taking care of your data, and you can transfer that slice of budget from OpEx to development investments.

On a more general level, data is one of a company’s most valuable assets, and plays a key role in all modern online and software products. This means not just data as code and images, and not even the data that flows when the service or product is being used. Storing and analyzing customer and usage data can tell companies how their business is doing and how they should be directing future development efforts. Building the capacity for this data storage is an investment that’s hard to scope out in advance, and analysis needs will evolve as the business grows and the market changes.

Open source for freedom

Things change all the time, and whatever service you buy may not be around for as long as your company, or they may change their terms without consulting you. Or you might just outgrow their offering and need a new provider. 

When buying your data infrastructure as a service, the one thing you want to ensure is that you’ll always have access to your data, even when you decide to switch services. The data also needs to be in a format that’s compatible with other providers and products, or you stand to foot a massive bill for conversion (if it’s even possible).

Here’s where open source is key. If you go with a service that offers fully open source products, your data will always be in a format that’s easy to export elsewhere, and it’ll be compatible with a wide variety of solutions. Open source gives you real freedom and flexibility to choose your providers and not be locked into a solution offered by a single company.

Shortening the innovation-development-testing cycle

Managed cloud databases are increasingly the key factor that enables quick innovation. Product development teams need a way to quickly turn ideas into testable products, and ready-made, managed infrastructure is the only way to achieve this in the IT world. The more building blocks you can buy ready-made, the quicker you can sketch out a test version of your dreams, and the quicker the roll-out when it’s finished.

DBaaS customers can provide data-driven services without having to build up the expertise in managing a new system and then having to build a datacenter. Their developers can quickly get to the part where they start programming, which greatly shortens the time to market. Being ahead of the curve by months can make or break a product, no matter how high its quality otherwise.

And speaking of quality–having the means to spin up data infrastructure quickly also means a company can continuously improve their products. With a DBaaS-sourced architecture, new environments can easily be set up for testing. 

This is equally true when the issue is not just improving upon or enlarging existing services, but creating entirely new products. The road from idea to product is much shorter when the  infrastructure is already built.

And lastly, it also means many teams can work on the same codebase simultaneously. This way the company can make every R&D penny count.

From CapEx to reduced OpEx

Then there’s the fact that datacenters cost money to build, and you’re using your CapEx to do it: it’s an investment in the most classical sense. Even if you’re leasing server space instead of building walls, you’re still spending your OpEx coins in a predefined amount of capacity and its maintenance. 

The amount of capacity a company maintains has to accommodate not just everyday use but also traffic spikes. When an investment is made (usually in some hurry) to increase capacity in response to an emergency need, it’s seldom considered safe to let go of it when the emergency passes because the process is painful and slow. This road usually ends with services overprovisioned by some 30-50% for regular use. And this is true whether you’re doing it with CapEx or OpEx.
CapEx reduction is easy to achieve by moving to a managed service, and there are plenty of them. But by selecting the right DBaaS, a company can make sure that their capacity meets their needs on a day-to-day basis: any service worth its salt will make it easy not just to scale up but also to scale down. It’s possible to reach a 70% reduction in infrastructure OpEx by managing your capacity and infrastructure properly. At the same time it lowers the threshold for using these services for new products, as well as retiring products that aren’t generating significant revenue.

Orchestration as a multiplier

There’s an African proverb: If you want to go fast, go alone; but if you want to go far, go together. Creating a standalone product to serve a single purpose is quick, but to provide real long-time value for your customers and your own company, versatile products or services that offer a range of functionalities and meet multiple needs are key. You might hit a goldmine by creating a single-purpose product or service that satisfies an urgent user need that no one else in the world has thought to satisfy, or you do it better than absolutely everyone else. It’s just not very likely, to say the least. 

A more robust business model is to target a wider customer base and meet a variety of needs. Versatile products are more useful to a larger group of people, and customers are more likely to want a solution that meets several needs at once. Even if you start small with a tightly targeted product or service, you want to keep the door open to expansion and innovation available in adjoining spaces.

The reason that products like this are harder to create and hence more valuable is that it means creating a heterogeneous data architecture that encompasses a wide range of building blocks. This is not easy, whether you’re building them in-house or buying them as a service. 

And making the components in your infrastructure all work together and pass data along flexibly is actually really hard. Companies that buy their data infrastructure as a service may have it even harder: using several services from multiple providers can add to the complexity of the overall architecture, and the range of available services can limit what it’s possible to accomplish. 

Note that the data flow itself is not an issue, since that can be configured; in some cases easily, in some cases less so, but it can be done, and then it’s only a question of how easy it is to add data sources. 

The bigger issue is the regular management and maintenance tasks, which can be a pain if you have to log into and out of multiple environments to check service status or perform updates. If your system management is fragmented, it’s hard to acquire an overall picture of the whole system, and that has implications for troubleshooting and optimization. 

Companies using orchestration systems like Kubernetes and Terraform to centralize and automate management tasks find that it enhances their control over resource consumption. With an orchestration system, companies can utilize a mixed set of services as easily as just one. These systems make it possible to centrally manage both individual services and the way the services interact. This gives a better overview of system status and performance and makes it quicker and easier to troubleshoot and fix issues. And of course, access management can also be centralized to an orchestration system, removing yet more regular upkeep tasks.

Kubernetes and Terraform also provide greater horizontal scalability. Instead of having to build endpoints into each service individually, it’s enough to build them in the orchestration system–and both of them also come with a wide selection of ready-made open source connectors, saving companies the trouble of writing their own.
This is how the benefit from orchestration combines with the benefit derived from increased agility in the marketplace and takes both to a whole new level. At Aiven, we see this all the time. Large numbers of our customers use Kubernetes and/or Terraform to save time, money and effort in terms of both system maintenance and product development.

Wrapping up

The common denominator for companies adopting managed cloud databases and combining it with an orchestration system is that they’re able to reduce their expenses markedly, due to a combination of reduced capital expenditures and smaller operating costs, even when taking into account the fees paid for their database management tasks. 

With a DBaaS in use, companies can also stay agile and responsive, and continuously evaluate and adjust their business model as the circumstances change. With OVHcloud’s managed cloud databases, powered by Aiven, you don’t have to worry about your database infra or administration, including set up, backups, scalability and security. This saves you time and money, so you can focus on building and deploying the cloud-based applications you want.

A large choice of “vanilla flavor” DBMS

The market is brimming with database engines, we will offer you this large choice over the coming months. Our Public Cloud Databases are of course fully managed and compatible with the full OVHcloud portfolio including bare metal for instance.

Did you know that delegating the setup and daily operations of your database cluster could help your improve your performance by 15% to 20%? That’s a pretty good argument to move your database to the cloud if it wasn’t already the case!

You might still wonder how these DBaaS differ from existing market offerings?

• Aside from MongoDB, all other engines are open-source so that you’ve got no risk of vendor lock-in and can adapt your technology strategy in the long run. We partner with the leader of open-source DBaaS, Aiven, to deliver this full portfolio.
• What’s more, we deliver the official, full and updated experience or “vanilla flavor” of each DBMS, and not a fork in our cloud environment. It means that you benefit from all the features, updates and community innovation.
• They are hosted in our trusted Cloud-Act free cloud infrastructure – in Europe and Canada today, and soon in other parts of the world – to ensure you full data privacy and infrastructure compliance. 
• Last, but not least, after the free beta, their pricing is fully transparent, predictable and much cheaper than competition. Why don’t you check our price list by yourself? What you see is what you pay! All costs including outgoing traffic are included. Don’t forget to multiply the price by the number of nodes!

You voted, we delivered

We know you have been waiting for these managed databases in the public cloud for some time, so we asked you which were your favorite ones and delivered them first. After 3 weeks of usage, here is our beta testers’ podium:

1. Almost half of our first beta testers use PostgreSQL. It’s the most advanced, extensible and highly secure relational database that you use for mission critical business applications. 
2. Another big third of our users are on MySQL, one of the most popular transactional engines for eCommerce platforms, but also an ideal choice for many web applications. 
3. Redis is the third favorite database with almost 15% adoption. It is frequently used for website caching and personalization, chat and messaging apps but also in the gaming industry for leaderboards.
4. The last few percent of users are on Apache Kafka , the must have distributed data streaming platform. Its horizontal scalability is useful  for IoT data ingestion, real-time analytics as well for event-driven applications.

But what do Kafka, MySQL, PostgreSQL, OpenSearch and Redis do?

Long story short: too many uses cases for one blog post! But let’s dive a bit into the main concepts and key differentiators.

Imagine that you are literally an e-commerce website… At least try to imagine 😀  It may be a little silly, but a good way to understand.

It’s almost Christmas, plenty of customers are creating accounts, ordering gifts, putting their credit cards. As a website, you cannot lose their information, you want to store it precisely. Here come relational databases to the rescue!

Relational databases with MySQL and PostgreSQL

Relational databases are widely adopted worldwide, with pretty simple tables, with columns and rows. Each table can be linked to others, with relationships, it’s called a schema.

The most famous ones are MySQL, PostgreSQL, MariaDB and SQL server.

The idea is always the same, tables and relations, with a goal to guarantee data validity despite errors, power failures.

Imagine that you, the website, receive an order for a new gift; you ask for a payment of 50 euros. The customer is paying, but just for 2 seconds your database is flapping and unreachable.

As a website, do you want approximate data? Do you want to be almost certain that the customer has payed? Certainly not! You want to be 100% confident about the transaction in your databases.

Relational Databases provide ACID guarantees (for Atomicity, Consistency, Isolation and Durability) that make them the best solution to deal with this kind of use case.

MySQL and MariaDB are often used for simple website and web application, such as WordPress.

PostgreSQL is more production grade-oriented, with full ACID compliance, advanced security and high availability (HA mechanism, and various extensions for various use case (geographical data, metrics, …).

Also, PostgreSQL is the only database system in the list owned by no company. It’s owned by the PostgreSQL community, you and me. Unlike MySQL that’s the property of Oracle for example.

Let’s come back to our e-commerce scenario!

It’s Christmas time for our website, your are now able to receive and store correctly your products, the orders, the bills… neat!

But wait… Now more and more customers are coming to you, asking ALWAYS for the same price and description of this wonderful pair of socks. Worst, they put a few products in the basket, but don’t buy them.

You are slowed down by storing and giving information from your local storage (images). In the same way, pushing in database information that you would not need to keep (basket) is frustrating. Last but not least, tons of requests in your relational databases (“SELECT Articles in discounted_prices…”) are always the same, giving the same results…

Grrr! It’s really painful to store this kind of ephemeral information. What if you could store and retrieve this data somewhere very, very fast?

Hello Redis™*! your best friend for caching data

The most handy database engine to answer your need is Redis™*.

Redis has two main characteristics: first, it stores data in volatile memory (RAM), not in classic storage such ad SSD drives. Second, it’s not a relational database, but a key-value store. You can store various type of data, such as HTML code, images, user sessions, gaming leaderboards, chat sessions, …

Each time you have to keep in mind that this data “can” be lost and you will store/retrieve it with huge performance.

Most popular use cases are website performance improvement, databases caching, gaming leaderboard, chat tools,.. Twitter, Snapshat, instagram, AirBnB, Pinterest.. they all use Redis!

The most handy database engine to answer your need is Redis.

Redis has two main characteristics: first, it stores data in volatile memory (RAM), not in classic storage such ad SSD drives. Second, it’s not a relational database, but a key-value store. You can store various type of data, such as HTML code, images, user sessions, gaming leaderboards, chat sessions, …

Each time you have to keep in mind that this data “can” be lost and you will store/retrieve it with huge performance.

Most popular use cases are website performance improvement, databases caching, gaming leaderboard, chat tools,.. Twitter, Snapshat, instagram, AirBnB, Pinterest.. they all use Redis!

Kafka, to avoid kafkaian situations

Apache Kafka, is the world’s most famous streaming tool. Imagine a highly-available and highly efficient platform, allowing you to connect to dozen data sources, “snif” the data in real time with near zero latency and push it somewhere else. That’s Kafka which unlike Redis is used a bit everywhere.

You don’t store information in Kafka, you connect Kafka to information sources. Then, of course, this data can be reused.

Main use cases are messaging between applications (it acts as a buffer), real time analytics and real time data pipelines, aggregation of metrics and logs (imagine a company with 1.5 million website ands 250’000 servers to monitor, for example ).

OpenSearch to keep en eye on everything

OpenSearch is an open source fork of Elasticsearch, allowing you to ingest data, such as all the logs of your website and easily analyze them.

Perfect for us to follow all the 404 errors for example! Wonderful dashboard in minutes, in real time!

Here is an example made with OpenSearch sample data:

The A-team of data ecosystem

As a website, you can think of relational databases, Redis, Opensearch and Kafka as the A-team. They are not similar at all; each of them has a specific role to play in the adventure.

At the end, I love it when a plan comes together!

Learn more about these use cases with Aiven’s Cofounder and CTO, Heikki Nousiainen, at Ecosystem Experience!

*Redis is a trademark of Redis Ltd. Any rights therein are reserved to Redis Ltd. Any use by OVH SAS is for referential purposes only and does not indicate any sponsorship, endorsement or affiliation between Redis and OVH SAS.