The word “NoSQL” stands for “Not Only SQL” and it is a type of database that differs from the traditional SQL database. A traditional SQL database is easier to understand than a NoSQL database because of the different concepts of the two types of databases. A traditional SQL database stores data in tables of rows and columns, with each cell of the table containing the data for one field. A NoSQL database, on the other hand, uses sets of unstructured data called “documents.” These sets are also called “objects” or “documents” and they are stored in a way that can’t be represented in a table of rows and columns. This is the fundamental difference between the two types of databases.
NoSQL Database Types
There are many different types of NoSQL databases, but three are the most popular. This article will briefly overview each type of database, including its strengths and weaknesses.
The first type of database is a document-oriented database. A document-oriented database is fairly simple to read and write, as there is no need to write SQL queries to search through. Documents can be created and updated as necessary, and they can be queried for use as well. However, as the database is not relational, it is not as easy to query as a relational database.
The second type of database is a graph-oriented database. Graph-oriented databases are also fairly simple to read and write, which has their advantages and disadvantages.
Benefits of NoSQL
NoSQL databases are highly scalable, low latency databases that are easily scalable. They are very fast but are not advisable for complex functions that are not asynchronous or atomic. This type of database is perfect for projects that require high performance. It also allows for more simplified querying, so the logic goes much faster than other SQL databases.
The views expressed on this blog are those of the author and do not necessarily reflect the opinions of Enteros Inc. This blog may contain links to the content of third-party sites. By providing such links, Enteros Inc. does not adopt, guarantee, approve, or endorse the information, views, or products available on such sites.
Are you interested in writing for Enteros’ Blog? Please send us a pitch!
RELATED POSTS
Inside a Fintech Outage: How 200 Milliseconds of Latency Reshaped Risk
- 31 October 2025
- Software Engineering
Introduction In fintech, performance isn’t just a technical metric — it’s a financial one.Transactions, pricing engines, credit scoring, fraud detection — they all run on milliseconds.But what happens when those milliseconds multiply? In mid-2025, a mid-tier digital lender experienced an unusual outage.Not a crash.Not downtime.Just slow time — an invisible 200 ms delay that rippled … Continue reading “Inside a Fintech Outage: How 200 Milliseconds of Latency Reshaped Risk”
Open Banking APIs: Where Performance = Trust
- 30 October 2025
- Software Engineering
Introduction Open banking promised to be a paradigm shift — enabling consumers to share financial data securely and allowing banks, fintechs, and third parties to build innovative services on that foundation. But as the ecosystem evolves, one truth stands out: it’s not just about access — it’s about performance. An open banking API that’s slow, … Continue reading “Open Banking APIs: Where Performance = Trust”
Enteros for the Travel Industry: Enhancing Cost Estimation Accuracy Through AIOps, Observability, and Cloud FinOps
Introduction In the fast-moving world of travel and hospitality, accurate cost estimation isn’t just a finance issue—it’s a performance challenge. From dynamic booking systems and real-time analytics to backend inventory databases and AI-driven recommendation engines, every operational layer relies on complex data interactions. The travel industry has always faced volatile demand, fluctuating operating costs, and … Continue reading “Enteros for the Travel Industry: Enhancing Cost Estimation Accuracy Through AIOps, Observability, and Cloud FinOps”
Transforming Data Lake Efficiency in the Technology Sector: How Enteros’ AI Performance Platform Redefines Database Optimization
Introduction In today’s data-driven technology landscape, the backbone of innovation lies in how efficiently enterprises manage and utilize their data. With the rise of big data, cloud ecosystems, and AI workloads, data lakes have become the central hub of data intelligence—storing massive volumes of structured, semi-structured, and unstructured data. However, as organizations scale their digital … Continue reading “Transforming Data Lake Efficiency in the Technology Sector: How Enteros’ AI Performance Platform Redefines Database Optimization”