Redis VS Apache HBase

The code uses the codehooks-js library to handle routing and middleware for the API, and the node-fetch library to make HTTP requests to the OpenAI API. The code also uses the built-in codehooks.io Key-Value store to cache the response from the OpenAI API for 60 seconds, in order to reduce the number of requests made to the OpenAI API (If you want to create your own Node.js Express backend, you just need to replace this cache with Redis for example).

Redis is an in-memory database and an open-source streaming engine with an IMDB data structure server that supports multiple data sets and data streams. This open-source platform has high throughputs and lower bandwidth due to its in-memory features that lead to faster processing of big data in data science applications.

Quirrel is a popular open-source webhook framework that makes it easy to add webhook support to your app. It makes uses of redis under the hood.

Redis

Redis is an in-memory data store that you can use as a database – or a cache in front of your regular database. The speed of Redis makes it ideal to cache database queries, complex computations, API calls, and session state.

I didn't finish college and I didn't see anything about Databases when I was there, so I don't have any theoretical background and on these 4 years coding at enterprise level my focus was totally in things like: Clean Code, SOLID, Design Patterns and other stuff code related and my only Database knowledge was about SQL/MySQL and Cache/Redis.

For the course I started to collect Open Source projects developed by corporations. There are a few where the product is open source such as Redis and Elastic. There are others where the company shares some of its code as open source such as Netflix, Facebook, or Booking.com.

The answer is yes. Introducing Redis, an open source database, in-memory, key-value data store and it is most-loved database by developers for five years running. Redis is commonly used as a primary database, cache, queue, and message broker. Redis is an open source (BSD licensed) that is used primarily as an application cache and quick response database and because the data is stored in memory rather than on a disk, Redis delivered unparalleled speed, reliability, and performance.

I'm not a C engineer, but I think I have an interesting recommendation to consider.

Since you are already familiar with other languages, you obviously don't need to know the basics of C. The basics are the same everywhere. Instead, you'd likely want to build that mindset on how to build good software with C.

I suggest you read other people's code and try to deep dive into the whys.

I heard Redis is a well-written software.

    git clone https://github.com/redis/redis.git

HBase, A scalable, distributed database that supports structured data storage for large tables.

Today, it is normal for enterprises to leverage diversified databases. In my market of expertise, China, in the Internet industry, MySQL together with data sharding middleware is the go to architecture, with GreenPlum, HBase, Elasticsearch, Clickhouse and other big data ecosystems being auxiliary computing engine for analytical data. At the same time, some legacy systems (such as SQLServer legacy from .NET transformation, or Oracle legacy from outsourcing) can still be found in use. In the financial industry, Oracle or DB2 is still heavily used as the core transaction system. New business is migrating to MySQL or PostgreSQL. In addition to transactional databases, analytical databases are increasingly diversified as well.

For this type of systems PostgreSQL not best solution, and for a number of reasons like lack of replication out of the box. And we strictly must not have «Vendor lock», and therefore also did not take modern SQL databases like Amazon Aurora. And end of the ends the choice was made in favor Cassandra, for this article where we will talking about low-lever implementation of Repository Pattern it is not important, in your case it can be any unpopular database like HBase for example.

Apache HBase

Wide column: Apache Cassandra, Apache HBase

The authors performed an analysis of critical failures of the five distributed systems: Cassandra, HBase, HDFS, MapReduce, and Redis.