# Navigating the Landscape of Database Engines: A Beginner's Guide

*We will discuss different types of engines, their use cases, pros and cons, and much more.*

Before jumping into the world of database engines, let’s first understand, **What is a database engine?**

To put it simply, it is just software **that performs CRUD operations and takes care of disk storage.** Some database engines are simple and only take care of storage and CRUD while complex engines can provide features like ACID support and transactions.

They are also known as **Storage engines.** Database Systems build features on top of these database engines.

Now that we know what a database engine is let’s start our discussion

### MyISAM

*Written in C, MyISAM was the first database engine for MySQL.*

* ISAM stands for Indexed Sequential Access Method. In this engine every **index that we create points to a row.** It uses B-tree for indexing.
    
* Since every index points to a row, **read operations are fast**. Even the **insert operations are fast because we are appending the new record to the end of the file** and we always know where the end of the file is. However, the main issue is with the update and delete operations. When we **update/delete existing rows, we change the row size, this changes the offset and all the index pointers need to change.** This is expensive.
    
* It provides **no Transaction support.**
    
* Database crashes corrupt tables and has to be manually repaired.
    
* It only provides table-level locking. If you want isolation you just have to lock the entire table.
    

### **InnoDB**

*It replaced MyISAM as the default database engine of MySQL and MariaDB.*

* In this engine, the B+ tree is used for indexing. Each index points to a primary key and each primary key points to a row. If there is no primary key then the engine makes one for you.
    
* It supports transactions and therefore implements ACID features.
    
* It also allows row-level locking so you don’t need to lock your entire table. This makes query processing faster.
    
* It also introduces a lot of new features like foreign keys, tablespaces, and spatial operations.
    

### SQLite

*It was designed by Dwayne Richard Hipp and written in C language*

![](https://cdn-images-1.medium.com/max/800/1*-rpVqC-6N4CCVSx0QzqVYQ.png align="center")

Image credit: [https://commons.wikimedia.org/wiki/File:SQLite370.svg](https://commons.wikimedia.org/wiki/File:SQLite370.svg)

It is one of the most widely used embedded databases and is used in web browsers, mobile applications, operating systems, etc.

* It used B-Tree for indexing.
    
* It allows all ACID features
    
* It allows table-level locking. It does not need row-level locking because it is usually used locally and there is only a single user.
    
* It allows concurrent reads and writes.
    

### LevelDB

*It was designed by two Google engineers Jeffery Dean and Sanjay Ghemawat and written in C++ language. It was inspired by Google BigTable.*

![](https://cdn-images-1.medium.com/max/800/1*3Ps_BIGZB0cSjgv2BNuMTg.png align="center")

* It is **not** a SQL database. It does not have a relational database model and does not support SQL queries.
    
* It used **Log-Structured Merge Trees for indexing**. It works **great for high insert volume**. (unlike B tree that may need to rebalance itself after insert which makes insert operations slow)
    
* It does not allow transactions.
    
* It is single-threaded
    
* There are levels of files and as the file grows large, levels are merged.
    
* They also support Write Ahead Logs to ensure durability.
    

### RocksDB

*It is a fork of Google’s LevelDB and is further developed by Facebook. It is used as MyRocks for MySQL, MariaDB, and Percona. It is also used by MongoRocks for MongoDB.*

![](https://cdn-images-1.medium.com/max/800/1*UVbIIe83Qfj3ZOyFYYgcBw.png align="center")

**Similarities with LevelDB**

* It also uses Log structured merge trees
    
* It is also key-value pair storage and does not support SQL queries.
    

**New features added to RocksDB**

* It allows transactions.
    
* It also used multi-threading to improve performance.
    
* Other features include Geospatial indexing, Bloom filters, merge operators, etc.