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?
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:
- Social applications
- Online ads
- Data archiving
Why Are NoSQL Databases Faster?
The biggest reason that these databases are faster is that they “focus on using a very small set of database functionality,” according to Cameron Purdy, who used to work at Oracle.
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
4. Amazon DynamoDB
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.