Top 10 Popular Real-Time Databases Perfect for Storing Your Data

Top-10-Popular-Real-Time-Databases-Perfect-for-Storing-Your-Data

Top-10-Popular-Real-Time-Databases-Perfect-for-Storing-Your-Data

The Top 10 Real-Time Databases that are used by large organizations have been around for a long time

While relational databases have been around for a long time, real-time databases are becoming more popular because they allow for real-time data storage and syncing with almost no latency.

Streaming platforms such as Netflix, Prime Video, and others, as well as companies managing large amounts of data, rely on databases. 

That can be monitored while also providing high security and encryption, and real-time databases are the preferred method. Check out the top 10 real-time databases used by large organizations, as well as some with a small architecture that can be used by startups!

 

1.Firebase

Firebase, a Google Developers product, is the rising star for real-time data storage and syncing. It is a cloud-hosted NoSQL database that allows for global app data queries. It includes mobile and web SDKs for developing serverless applications, and users can also run backend code to receive responses from database-triggered events. Firebase, in addition to providing strong security through authentication, is optimized for offline use by storing data on a local cache, which is then uploaded and synchronised online when the device is connected. Firebase has a higher latency of around 100 milliseconds when compared to Redis and others.

 

2.Aerospike

Aerospike is another popular NoSQL real-time database that allows organizations to work across billions of transactions in seconds. It is designed for multi-cloud, large-scale JSON documents, and SQL use cases. It has the smallest footprint due to its patented Hybrid Memory Archit 1 millisecond pike has less than 1-millisecond latency for storing 2 TB of data, but it does not store data in memory. When compared to other real-time databases, it requires 80% less infrastructure to operate, making it ideal for smaller businesses

 

3.Hazelcast

Hazelcast, a real-time data stream processing platform, allows you to create applications and take immediate action. It can be written in Java, Node.js, Python, C++, and Go. Hazel can be used for a variety of applications, including retail banking, AI operations, and supply-chain logistics, among many others. It is cloud-independent, with an average latency of around 2 milliseconds for 18k/s throughput.

4.Redis

Redis is a popular and dependable real-time database for speed and simplicity, with a highly scalable caching layer for optimal enterprise performance. It can also identify data using AI-based transaction scoring to aid in fraud detection. It’s most commonly used for caching, message brokers, and database deployment across cloud and hybrid environments. Redis boasts a latency of 200 microseconds for a 1GB/s network. It is available in all languages and runs on macOSX, Linux, Windows, and BSD.

5.RethinkDB

RethinkDB, an open-source, scalable database, simplifies the process of building apps as well as the laborious process of managing data. It enables you to query JSON documents in dozens of languages and create modern apps using technologies such as Socket.io and SignalR. The simple API for precise control allows you to scale your app clusters with a few clicks using the intuitive web UI. RethinkDB completed a 16-node cluster with a latency of 3 milliseconds, outperforming many of its competitors.

 

6.Kafka by Apache

A distributed event streaming platform with open-source pipelines, streaming analytics, and data integration. Kafka can work with Postgres, JMS, Elasticsearch, AWS, and many other databases thanks to its built-in stream processing. Kafka is extremely scalable, with a latency of fewer than 2 milliseconds for clusters of machines, and it can be integrated with other real-time databases such as Hazelcast and RethinkDB, among others.

 

7.Amazon Web Services Kinesis

Amazon’s Kinesis, which makes it easier to process and analyze collected and real-time data, is managed on the AWS server, demonstrating its scalability. It supports data buffering and runs fully managed on streaming applications. This database’s most notable application is for developing video analytics applications. Kinesis is an excellent tool for developing application monitoring, detecting fraud, and displaying live leaderboards.

 

8.Oracle

Larry Ellison, a young software engineer, was particularly inspired by the paper (current CTO of Oracle Corporation). In 1979, he developed Oracle, the world’s first commercially available RDBMS system. Oracle has remained the leading commercial RDMBS system and has dominated the Unix and Linux systems since then. Oracle has evolved over the last 41 years, contributing to RDBMS and overall database System innovations.

9.PostgreSQL

In 1986, the legendary Michael Stonebraker led the POSTGRES (Post-Ingres) project to address the problems of existing database projects. PostgreSQL emerged from the POSTGRES project, which was a Relational Database Management System. PostgreSQL has led the way in modern database development for the past 30 years, contributing many innovations, and Michael Stonebraker received a Turing Award in 2014 primarily for his work in PostgreSQL. PostgreSQL is now one of the most widely used databases. Furthermore, it is the most advanced Open-Source Relational Database.

10.MySQL

Michael Widenius and David Axmark, two software engineers, created the Open-Source Relational Database Management System (RDBMS) MySQL in 1995. MySQL quickly gained popularity in the industry and community due to its enterprise-grade features, free, flexible (GPL) community license, and upgraded commercial license. Among open-source databases, PostgreSQL emphasizes innovation and advanced features, whereas MySQL emphasizes robustness, stability, and maturity. MySQL is now one of the most well-known and widely used SQL databases. It’s also one of the most commonly used databases in web applications. MySQL is used by some of the world’s largest Web-Scale applications (for example, Facebook and Uber).

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