Structured and unstructured data are not an either-or scenario. Instead, it’s a matter of matching the data type to your application and its needs. Each serves a purpose and has advantages and disadvantages.
Get a better idea of when to use structured and unstructured data and some of the benefits of each.
What is Structured Data?
Structured data generally lives within a relational database. Big data is processed using relational/SQL databases where each field of information is in length-delimited data.
Some data is machine-generated. This might include information from the following sources.
Satellite imagery that powers weather information or informs military movements
Scientific information, such as seismic images or space exploration data
Surveillance photos or video
Data from sensors, such as traffic or weather data
What’s the Difference Between Structured and Non-structured Data?
The biggest difference between structured and non-structured data lies with the analytics.
The obvious difference is in how and where the data is stored. Unstructured/Non-structured data is generally in a NoSQL database while structured data is in a relational/SQL database.
But the difference in the experience with the data is in analytics. Data processing programs can provide much deeper analytics for structured data than you can with unstructured but that’s not to say you will have no analytical capabilities with non-structured data.
Emerging tools make it so that unstructured data reacts similarly to structured data, but at much faster speeds with the opportunity to scale quickly. These tools make it possible to analyze sentiments as if they were a black and white piece of data like a ZIP code.
Learn more about how AI is changing NoSQL databases and download BangDB, a NoSQL database that employs machine learning to make unstructured data searchable and usable.
Today’s IT requires ample storage. But the challenge with today’s storage needs is that they fluctuate. And even companies that have steady database needs require large amounts of storage where managing databases in-house can be time-consuming and expensive.
As a result, most companies look to database-as-a-service providers to fulfill these needs. Databases can serve many purposes but the great benefit of using a DBaaS is that your technology team won’t have to handle the ongoing upkeep and security updates for these databases.
Database rental has many great benefits for consideration when evaluating your needs. For example, some companies use a hybrid model of on-premises databases mixed with managed cloud databases.
We’ll explain what database-as-a-service is when you should use it, the many benefits you can enjoy from this service, and the top DBaaS providers.
What is Database-as-a-Service?
The simplest example of what database-as-a-service is that many people understand is Google Drive. Google Drive allocates a set amount of storage to each user. Within the storage, you can create folders and structures to meet your needs.
Likewise, many databases offer structure and processing as part of their storage services. DBaaS encompasses many different services that you likely use every day and think nothing about.
In a sense, website hosting is a database-as-a-service offering a specifically structured database service that renders your website to visitors when they type the URL.
But there are far larger databases available to meet the needs of businesses and developers. These databases can come in many different types including:
NoSQL
MySQL
PostgreSQL
Different types of databases are more scalable than others. NoSQL is the most modern DBaaS offering options that will grow with your company and applications quickly.
When you purchase a DBaaS subscription, you’ll get all the necessary tools to manage a cloud-based database. These tools include licenses, provisioning, maintenance, and ongoing support.
Cloud-hosted APIs make it possible for developers to create applications in the cloud and write and read data from those cloud-based databases.
The benefits that a database-as-a-service offers are immense and impactful for most organizations. Here’s a look at these great benefits.
Excellent service quality: to get access to a cloud-based database, you’ll agree to a service level agreement that outlines the performance and support that comes with your subscription. As such, these database companies must meet these high standards and uphold security guidelines. The availability of the database must match what is outlined in the service agreement.
Fast deployments: your in-house resources will no longer have to worry about administrative tasks. Instead, they can focus on innovating for your company and deploying those innovations to aid in business growth instead of focusing on keeping systems running.
Flexibility: as your need for resources changes, it’s easy to upgrade or decrease your database usage. Most DBaaS companies charge based on usage, which means you won’t have to worry about changing licensing agreements or subscription levels from month to month as your needs change.
Quick provisioning: most database-as-a-service providers offer self-service capabilities so that you can get started quickly with just a few clicks. That way, you don’t have to worry about governance or administrative responsibilities.
Improved agility: business requirements can change from one hour to the next. With on-premises solutions, you might need a deployment to address new requirements. But DBaaS allows you to be much more agile to meet changing needs and requirements.
Outstanding security: DBaaS providers handle the security side of things, which means you won’t have to worry about keeping the database updated to protect your valuable data. These providers offer multi-layered security to protect data at rest.
Get Started with BangDB NoSQL Database-as-a-Service
BangDB is a leading NoSQL DBaaS. With artificial intelligence to help you identify and solve relevant problems facing your organization. The database natively supports AI and streaming services to allow you to log events to evaluate patterns in real-time.
Fast NoSQL Databases: Data is all around us and extremely plentiful. Just about everything that a consumer does generates data now. From posting to social media to purchasing groceries online for in-store pick up, modern-day databases need to be prepared to cope with these extreme data volumes.
The best way to cope with large data volumes is to use a distributed database capable of operating different nodes to partition data accordingly. That way, if one node goes down or is overloaded, the system can continue to run using other nodes with no problems. Fast NoSQL databases are also needed in order to keep up with the speed of the data streaming from multiple sources and also for real time processing of the data
Answering these challenges means using a fast NoSQL database that can handle partition tolerance seamlessly to create a great experience for customers while housing the information data scientists want.
What Is a NoSQL Database?
A NoSQL database does not mean that there is no relationship between data at all. NoSQL actually stands for “Not Only SQL.” This means that information stored in this type of database is not divided into various tables. That way, you can see all related data without specific restrictions.
NoSQL databases allow data scientists to view data in one structure. This enables the data processing to experience greater speeds and fewer performance lags. Completing multiple queries at once with these databases should be no problem and you won’t need to run joins.
Using a NoSQL database continues to grow in popularity because they scale extremely well and are ideal for distributed environments. Your team can rely on these databases to perform well under heavy workloads time and time again.
Are NoSQL Databases Faster?
NoSQL databases are faster and were designed for performance out of the box.
Yes, NoSQL databases are faster and designed for high-performance data processing. Developers created these non-relational databases out of a need for greater agility and performance while also scaling daily to meet the needs of ever-increasing data processing and storage.
NoSQL databases can help with real-time predictive analytics and meet the needs of billions of users.
As you go about your daily routines of surfing the internet and using mobile applications, you’re probably engaging with these lightning-fast databases. Some common uses for NoSQL databases include:
Ultimately, the speed of your database will depend on how you’re using and querying that data. Some software engineers develop SQL applications that can act and function similarly to NoSQL, but it still leaves the question of the scalability of such ad hoc creations. And you’ll need to plan for longer development timelines to accommodate such engineering.
5 Fast NoSQL Databases
If you’re looking to increase the speed, reliability, and scalability of your database solutions, here’s a look at the nine fastest NoSQL databases available.
MongoDB is an excellent database for storing documents in JSON objects. Large companies like Uber and eBay use their services. Its ideal use cases include the following.
Integration of hundreds of data sources with a unified data view
The need for large read and write operations
Storing clickstream data to analyze customer behavior
The company offers extensive online training and certification programs to help its users learn the database and use it to its fullest.
Cassandra is an open-source NoSQL database. Facebook initially developed Cassandra but now it’s widely available and many companies use it because of its scalability.
Cassandra is well-known for its ability to handle petabytes of information. It is also a great product for responding to thousands of requests at once.
Data scientists often choose Cassandra in the following scenarios.
Situations where they have more write operations than reading operations
Greater availability needs than consistency needs. Facebook built it to meet the needs of social networking, but the application would not do as well for banking
Fewer joins and aggregation database queries
Some examples of applications that lend themselves well to using Cassandra include weather data, order tracking, health tracking
Elasticsearch offers one of the best full-text search databases. It is open-source and highly scalable. You can use Elasticsearch when you need fuzzy matching.
Some major companies like Slack and Medium use Elasticsearch. The database is ideal if you’re looking to accomplish the following functionality.
Full-text search use cases
Chatbots to resolve queries, especially using fuzzy matching in the case of misspellings or poor syntax
Storing and analyzing log data
Choosing the right database will have an enormous impact on the speed of your project.
Amazon’s product is not open source, but it is still highly scalable even with up to 10 trillion daily requests. It’s no surprise that many large companies like Snapchat and Samsung use Amazon DynamoDB.
This NoSQL database has two major use cases.
Simple key-value queries with high volumes
OLTP workloads that require highly consistent data, such as online banking or ticket booking
BangDB is a very high-performance database in the world. It has been designed and developed from the ground up to deal with modern and emerging fast-moving data in real-time. It implements core features of a database like transaction, concurrency, WAL, indexing, etc. and at the same time implements AI, Graph processing, and Stream processing natively within the database for modern user cases
BangDB is ideal for the following use cases.
Real-time data processing and analysis
Random and real-time data access
Predictive and enhanced data science with Graph
Scalable, Reliable Database Solutions
NoSQL databases offer some of the fastest, most reliable, and scalable solutions. Start building your modern data app today.
There are more than two dozen NoSQL databases on the market today. With so many options, it’s hard to know whether you’re choosing the right NoSQL database.
Ultimately, selecting a good SaaS database comes down to how you’re using the data. Each database uses a different architecture and therefore has different functions. So the first step in selecting a database is understanding the options.
Tip 1: Learn the Advantages of NoSQL Databases
Before deciding that a NoSQL database is right for your SaaS application, learn more about the benefits and advantages of a NoSQL database.
Scalability: NoSQL databases use low-cost commodity hardware that makes them easy to scale.
Large data handling: The databases can handle large data volumes since they are distributed.
Dynamic schemas: You don’t need schemas to begin working with data.
Lower cost: Since these databases use commodity hardware clusters, they allow you to transact and store large data volumes at a low cost.
Auto-sharding support: Spread data across any number of servers easily with NoSQL databases.
Tip 2: Know the Limitations of NoSQL Databases
Although NoSQL databases have many great advantages, they also have some limitations. One limitation is that they are not as reliable as relational databases. For example, most NoSQL databases do not support ACID natively, meaning you’ll need to use your own code to do so.
You’ll need manual query language since your database isn’t compatible with SQL. This can slow down your system and make it more complex.
Finally, NoSQL is newer than relational databases, meaning they are not as stable and feature fewer capabilities as an emerging tech option.
Tip 3: Understand the 4 Types of NoSQL Databases
Understanding the pros and cons of each database will help you make the right decision from the beginning.
Tip 4: Evaluate Current Structures and Transitions
If you have an existing web application that you’re looking to transition out of a relational database into a NoSQL database, consider your current structure and what that transition might look like.
You might need several different NoSQL databases or microservices to transition out of your relational database without serious service disruptions or errors.
An incremental approach to database refactoring can ensure a seamless and simple transition.
Make a plan for how to move away from your current database or databases in favor of the more agile NoSQL options. It might take some time to make the transition, but you’ll get faster response times and simpler scalability with the move.
Tip 5: Learn What NoSQL Databases Are Best At
Some scenarios lend themselves to the right NoSQL databases better than others. Here’s a look at some scenarios and application requirements that might lead to selecting this type of database.
Tip 6: Consider Long-term Use Cases
Future-proof your product by thinking through what your needs will be several years from now.
Avoid being shortsighted in the long-term use of your databases. Look down the road several years to consider how you might use the data in different ways and with increased volumes.
Choosing a database that only fits your needs today can mean a great deal of work and rework later on. Some types of NoSQL databases lend themselves to adapting and scaling better than others. Review possible needs as your company grow and develops to have a better understanding of your long-term needs.
Tip 7: Which is the right NoSQL Database for a Web Application?
With all the planning and research phases behind you, you can move on to choosing the right NoSQL database. There are more than two dozen available currently, but we’ve put together a listing of some of the best.
Download BangDB to Power Your SaaS Applications
BangDB is a powerful NoSQL database that can power various types of SaaS applications. With AI built-in, you can use deep learning to power custom experiences. Download BangDB Community now to learn more or consider an Enterprise license for added features and support.
