NoSQL Hosting: Delightful Database Hosting. Here’s Where To Find It In 2020.
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NoSQL Databases and Hosting
NoSQL is a catch-all term for technologies and database management systems that handle unstructured data.
You may have heard of these since the NoSQL movement has been gaining traction and attention recently (especially in the world of Big Data).
Before we dig into what NoSQL is and how you should choose to host it, let’s start with the basics.
What is NoSQL?
Data exists in two forms:
- Structured, which is generally better for record-keeping
- Unstructured, which is generally better for large, dynamic applications
You will sometimes see semi-structured data, which is a hybrid of the above.
The term NoSQL is generally interpreted as Not Only SQL. SQL refers to a part of the most common type of relational database management system (RDBMS), a Structured Query Language (SQL) database.
As its name implies, it tends to handle structured data.
NoSQL Options
You’ll find many options offered, such as Amazon Simple DB, Redis, MongoDB, and Apache’s Cassandra.
In some cases, you’ll even see legacy SQL vendors providing options, such as the Oracle NoSQL Database.
SQL vs. NoSQL
NoSQL database (or in-memory database) management systems are a large class of data storage tools that use various methods and models for storing and structuring data.
However, the one thing they all have in common is that they do not use a relational table system for structuring the data they store.
NoSQL Tends to Be Faster
Compared to relational table systems, NoSQL databases, regardless of whether they are hosted on the cloud or more locally, perform much better than their traditional counterparts especially when performing operations like reading, writing, or searching.
Sometimes Other Factors Affect Speed
However, there are instances where NoSQL databases lag – in the end, overall speed is likely to depend on your specific needs and implementation.
You may also need to learn things like XML or JSON.
Are There Alternatives to NoSQL?
There are certainly more complex options, such as graph databases and multi-model databases for those (such as engineers involved with NoSQL data modeling projects) who really have a need for speed.
However, it is also good to keep in mind that there are performance differences between different types of NoSQL databases as well – not all NoSQL databases are created equal!
How Relational Databases Work
A relational data structure organizes data into a grid of information where:
- Columns indicate the name of the data being stored
- Rows are where individual data object entries exist
In this regard, the results of a SQL query looks like a spreadsheet. If a row of data is missing information, that spot in the table either shows up as empty or NULL.
Data in other tables can be looked up via an identifier located in a column of another table, thus making the tables relational.
How NoSQL Data Stores Differ from Relational Databases
For a NoSQL database management system (which utilizes in-memory databases and is considered to be non-RDBMS), information organization does not follow the conventions of a relational database.
Instead of being boxed into a bunch of tables, NoSQL data exists in a more open format, which can be more easily distributed across a large number of physical computers.
Multiple NoSQL Systems and Technologies
In fact, there are actually several different technologies that could fall under the NoSQL umbrella.
Each option comes with its own strengths and weaknesses, but what all these NoSQL options have in common is the reliance on key-value pairs.
Key-Value Pairs
Key-value pairs are data attributes that exist as a data name (or key) that is paired with the data value (which is simply referred to as the value).
For example, one key-value pair might look like this:
{
address: "123 Main Street"
}
In this case, the key is ‘address’ and the value is ‘123 Main Street’.
The Advantages of NoSQL Databases
Though relational database management systems (RDBMS) and relational models have been in use for quite some time and are.
If in some ways, this is industry standard, why is there such a shift toward NoSQL databases?
A relational database system requires that the data model or data scheme is well-defined, designed, and implemented before the application is used and data stored.
This requires a great deal of development and research time and constrains the data model to the decisions made in development.
NoSQL Offers a Flexible Data Scheme
NoSQL databases usually do not have a strict data model, so the structure of the database can emerge over time as the application evolves and the data is collected.
This allows those implementing a NoSQL database to launch much faster than those working with a relational system.
The NoSQL database is also able to evolve more as time progresses.
NoSQL is Capable of Providing Structure to Unstructured Data
On a similar note, relational databases are designed to model systems that can map onto a highly-structured data model/schema. This can work:
- Very well for some real-world domains (such as products in an online store)
- Reasonably well for others (like items in a library)
- Not well at all for others (such as the content of websites across the entire internet)
NoSQL databases can provide structured storage of unstructured data, allowing the modeling of a more complex system.
NoSQL Offers Faster Read and Write Speeds
NoSQL databases are usually much better at writing large amounts of data and dealing with massive stores of data.
NoSQL utilizes sharding, which is a method of sharing data across multiple machines, better than relational databases.
Furthermore, complete information about specific items in the database can often be obtained without access to the entire database structure, because data isn’t smeared across a large number of interrelated tables.
For these reasons, NoSQL databases have been at the forefront of the Big Data movement.
The Disadvantages of NoSQL Databases
With that said, NoSQL is not the end-all-be-all of databases. NoSQL does come with some fairly significant downsides.
In some cases, the more traditional approach of using a relational database option might be the best choice (even if it might seem less “cool”).
Data Consistency
Relational data modeling involves creating a detailed structure of how data interacts and relates.
The schema itself provides information about the data domain, and it enforces adherence to the specified data model.
When done well, this ensures consistency in the data. There is only one “source of truth” for any particular fact, no matter how trivial that fact is.
The data and the schema interact to create a body of knowledge in which any particular question can only be answered one way.
ACID
In computer science, there is a concept called ACID. ACID stands for:
- Atomicity
- Consistency
- Isolation
- Durability
ACID, as a mnemonic device designed to help you remember the set of properties listed above.
If the database performs a sequence of operations that satisfy the ACID properties, you can be assured that your data is valid.
Even if things get interrupted by a power outage, connection disruption, and so on.
Here are brief definitions of the four ACID properties:
| Property | Definition |
|---|---|
| Atomicity | Transactions are all or nothing; if any part of the transaction fails, everything fails |
| Consistency | The transaction will change the database to another correct state – that is, an operation, such as writing data, will not result in the database ending up in a state that is not allowed (per database parameters) |
| Isolation | If a series of transactions occur simultaneously, then the end state of the database must be the same as it would be if the transactions occurred one-at-a-time in series |
| Durability | Completed transactions are never revered, even in the event of a disaster |
So, now that we spent all that time discussing ACID, how does this relate to databases (and NoSQL databases in particular)?
Acid Compliance
There are plenty of discussions on Stackoverflow around ACID and NoSQL.
ACID-compliance is something you should strive for if you need immediately consistent data (that is, your database should reflect the truth always and immediately).
For example, bank account balances are an area where immediate consistency is of utmost importance, as is ACID-compliance.
However, the debate rages on the internet as to whether NoSQL databases are ACID-compliant (or even if they can be made ACID-compliant).
Do You Need an ACID Database?
The specifics of this debate are outside the scope of this article, but if you are considering a NoSQL database, we encourage you to consider whether you need an ACID database or not.
If so, and if you are interested in pursuing a NoSQL database, you will likely need to spend time on how you can implement a non-RDBMS in a manner that meets the needs of your use case.
Generally speaking, you are more likely to have an easier time with an ACID-compliant implementation with a non-RDBMS. But as technology changes, this gap may close.
NoSQL Databases and the (Potential) Lack of Data Consistency
NoSQL databases do not generally enforce any particular schema, and adherence to a consistent data model is structurally impossible.
This opens the possibility of data inconsistency, either in the data itself or in the data design.
It becomes a requirement of application code to ensure that data is kept internally consistent and normalized.
For these reasons, NoSQL database systems usually are not appropriate for applications where a high degree of consistency and data-integrity is required.
Good examples are online banking or other financial services applications.
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Types of NoSQL Data Stores
There are five major types of NoSQL data stores (or databases), all of which work somewhat differently:
| Type | Description |
|---|---|
| Key-Value-Based | Though all types of NoSQL databases use some form of key-value pairs, a database that is explicitly a key-value store uses this type of data exclusively. The exclusion of all other data times significantly reduces complexity |
| Column-Based | Columns refer to three pieces of data: the unique name, value, and timestamp. A column can be a part of a ColumnFamily, which bears some resemblance to a row in a relational database |
| Document-Based | With document-based databases, data are encapsulated in either XML or JSON. Individual objects are structured somewhat into XML tags or JSON key-value pairs, which creates a document that is then stored |
| Graph-Based | A type of abstract storage that uses a concept known as a “triplestore” to build up semantic bindings between each element |
| Multi-Model | A multi-model database might include features of a graph-, document-, and key-value-based methods, for example. An advanced option, the user can define the models that exist |
More About Document Databases
As we just discussed, there are a number of NoSQL database types, such as key-value stores, tuple stores, object-oriented databases, document-oriented databases, and graph databases.
One of the more common NoSQL technologies used, especially for web content applications, are document databases.
If you plan on using a document-oriented database, you will want to brush up on something like JSON or XML.
Each document-oriented database works a bit differently, but in general, they store records as JSON-encoded documents.
A single “real-world” item (such as a book) is represented in document databases as a JSON document (rather than a row).
The entire set of such records is usually referred to as a collection.
Information Contained in a Document
In a document-oriented database, all the relevant information about a record is stored directly in the JSON document.
For example, in a blogging application, a single JSON document might store the Author’s name, the test of the post, the associated tags and metadata, and even the comments.
The comments would be individual JSON documents, embedded into the larger JSON document.
This is quite different from a relational database management system (RDBMS), where the comments would be stored in a separate table, and the author reference would be a foreign key.
The Downside of Document-Oriented Database
One major problem with this method of storing data is that any changes (such as the author’s name), you would have to make corrections on all the documents that mention it, rather than only in one place.
Moreover, these changes would have to be managed by application code, which requires developers to keep track of the data model separately from the database.
Luckily, many modern programming languages, including JavaScript, include things like JSON serializers or tools for working with XML to help.
What NoSQL Options Are Available?
The most prolific individual technology is Apache HBase, which originated from the Hadoop movement and has strong architectural ties to Google’s original Big Table.
Document Databases
Document databases like MongoDB or CouchDB are commonly used, which makes them very attractive for rapid prototyping.
This is because NoSQL document databases don’t require setting up the data structures before use.
Data-as-a-Service Options
Data structure services (such as Redis) are among the most popular key-value databases.
In fact, some, including Redis itself, is free to use, so you can try things out before you commit to a NoSQL platform.
Redis and its ilk are pretty different ways of thinking about data, and a free trial never hurts.
Such services are offered by many cloud providers and perform very well because the data is stored in memory and can scale up as needed.
The more exotic graph databases and multi-model NoSQL selections, however, are generally reserved for search tools or other applications that require data control for artificial intelligence.
How to Choose a NoSQL Database System
With five types of NoSQL databases to choose from, selecting the right technology for your use case is a matter of application appropriateness.
Moreover, some technologies exist as an instantly deployed cloud service while others require custom setup but allow for deeper control.
Your infrastructure may dictate which options are viable, and which ones are not.
In the section below, we will delve into the benefits and drawbacks of each type of system.
Where to Get Started with NoSQL
For someone who is unfamiliar with key-value data stores, the best advice might be to create a test application following tutorials and using open source application templates from Github – it is also probably a good idea to save the complex graph databases for later.
With regards to specific technologies, MongoDB and CouchDB are two that can be set up easily on a local computer (including your own) and used to create page prototypes quickly.
MongoDB
MongoDB is free, open source, cross-platform, and document-oriented (using JSON).
As an open source product, you are free to use MongoDB however you’d like.
However, there are several different products under the overall MongoDB umbrella that you might find useful if you’d like to have someone manage some of the infrastructure/logistics involved.
To use any of these options effectively, you’ll want to sharpen up on your knowledge of APIs so you can work with the MongoDB API.
Mongo has what is called the Mongo Shell, which users can use to practice commands directly from command line.
Apache CouchDB and Cassandra
Another open source option available that is good for beginners is Apache’s CouchDB.
With CouchDB, users can access some functions similar to those in MongoDB with “Curl” commands – but Couch also has a visual interface that allows users to actively create MapReduce (CouchDB’s API) logic.
CouchDB is not the only NoSQL product under the Apache umbrella.
Its sister product, Cassandra, is a good option for beginners as well. Cassandra is a column-based model, whereas CouchDB is a document-based model.
Other Technologies
Both MongoDB and CouchDB are amazing for learning and work well for live applications.
Most technologies, however, will have good walk-throughs for first-time users. As such, the best thing to do is pick a walk-through that you find easy to understand and follow that until you understand the concepts well.
Which NoSQL Option Should You Choose?
Finally, which NoSQL option is the best?
Well, the choice to use a NoSQL database (and which one to use) should be based on the specific requirements and use-cases of your project.
There are many vendors out there, including Cassandra, Amazon SimpleDB, Redis, Oracle NoSQL Database, and MongoDB offering options, so you are sure to find one that is right for you.
You should also keep an eye on NewSQL databases – relational database management systems (RDBMS) that build on the scalability and performance advantages of NoSQL databases.
Choosing a Host for NoSQL
If you decide to use a NoSQL option, either cloud-based or not, instead of a more traditional relational database management system (RDBMS), what should you consider when purchasing web hosting?
Installation of NoSQL
With so many NoSQL systems to choose from, the installation method you use when it comes time to set up your web hosting server depends on which platform and tools you’ve selected.
We do want to note that a NoSQL database does not need to run on the same servers as the one hosting the web application.
Many developers set up their databases on a different server than their applications and communication between the two occurs across a secure external connection.
Cloud Service and Maintenance
Many NoSQL solutions and technologies (especially those that are production-ready for apps) are almost always based on a cloud service provider, which means the servers themselves are not maintained by the site developers – they are maintained by the service provider.
Usually, NoSQL systems as cloud services work best with a Software-as-a-Service (SaaS) type of setup.
However, for more complex tasks, a virtual machine image can be used to quickly set up a virtual private server (VPS) with the desired NoSQL database (DB) installed, as well as all technical dependencies.
You can install NoSQL DBs manually, and doing this is often required for setting up a local copy for development purposes.
Hosting Support
As we mentioned, it is not essential that you host your NoSQL database on the same server as your application.
In fact, you might find it advantageous to do so depending on how your app works.
Regardless, it is a good idea to look for a host that actively provides support to hosting customers using NoSQL databases. Some good options for you to look into include:
Top 3 Hosts for NoSQL
The tool above can be used to search for hosts based on specific features. However, there are three hosts that stand out for NoSQL.
A2 Hosting
One of the most popular hosts, A2 Hosting is affordable, offers 99.9% uptime, and is fast.
Everything you need when running NoSQL.
SiteGround
SiteGround hosting for NoSQL.
This host offers top-notch uptime, great support, and affordable pricing.
Before you make the choice, I highly suggest considering if this host has the ability to scale for you.
For smaller amounts of data, SiteGround is a fantastic host.
iPage
VPS hosting is ideal for hosting NoSQL systems, and iPage offers more power and flexibility through their VPS packages than other hosting companies.
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SiteGround plans support NoSQL with fast speeds and excellent customer support. Right now you can save up to 67% on their plans. Use this special discount link to get the deal.
Final Thoughts on Hosting for NoSQL
The traditional and more commonly-used database systems are table-based relational database management systems (RDBMS) that use SQL (structured query language) for schema design and data querying.
However, non-relational databases, which are collectively referred to as NoSQL databases, have become increasingly popular for use with certain types of applications.
This is true especially in the world of Big Data. You’ll find options ranging from open source MongoDB to more enterprise-friendly options like the Oracle NoSQL Database.
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