MongoDB and Mysql: Which one is a better fit for me? Room 204-2:20PM-3:10PM

MongoDB and Mysql: Which one is a better fit for me? Room 204-2:20PM-3:10PM

About us Adamo Tonete MongoDB Support Engineer Agustín Gallego MySQL Support Engineer

Agenda What are MongoDB and MySQL; NoSQL and Relational concepts; Main differences between MySQL and MongoDB; MongoDB and MySQL similarities; Query Language; Performance comparison; Security; Best usage cases; Q&A

What are MongoDB and MySQL

What is MongoDB Document Oriented Database NoSQL Open source It is currently the most common NoSQL database out there. High Performance Database Different storage engines for different use cases

What is MySQL Relational Database Management System The "M" in LAMP stack Second most popular RDBMS According to DB-Engines' ranking Its architecture supports use of different storage engines Many different kinds of topologies used: Master - Slave Master - Master (active and passive) Multimaster - Slave Ring replication Tree or pyramid Multimaster Cluster (Group Replication or Galera Cluster)

NoSQL and Relational concepts

Database Concept A database is an organized collection of: Data Schemas Tables Queries Reports Views Other elements. Wikipedia

Relational Database Concept Written in the early 70s Records and attributes define relations Uses normalizations SQL Language Procedures Triggers Foreign keys Transactions - ACID

Non-Relational Database Concept Started in the 2000s; Non-relational concept. No tables or normalization; Query language is different than standard SQL; Made for new programming languages. Fast development; Relies on CAP theorem.

Main differences between MySQL and MongoDB

Differences between MongoDB and MySQL Some features we will compare: Normalization Transactions Query language Data storage and retrieval Indexes differences How to distribute and scale

How different is MongoDB from MySQL/RDBS NoSQL and SQL are not enemies they are meant to complete each other While MongoDB is a young NoSQL database, MySQL is a mature relational database. In some cases, using MongoDB as the main database is not the best thing to do. However, MongoDB can offer a very fast growing environment without too much effort.

How different is MongoDB from MySQL/RDBS Comparing Data distribution: MongoDB expects data to grow beyond machine limitations. MySQL does have a few add-ons to allow data distribution among instances. MySQL expects to work in a single machine (at least for writes). MongoDB doesn't allow ACID transactions, but it works with the CAP theorem.

Normalization Normal forms MongoDB features best practices to organize your data, but there are no hard rules to do so. MySQL strongly suggests using 3rd normal form (3NF) to avoid data duplication.

Normalization @ each intersection is a single scalar value

Normalization { } "_id" : ObjectId("507f1f77bcf86cd799439011"), "studentid" : 100, "firstname" : "Jonathan", "middlename" : "Eli", "lastname" : "Tobin", "classes" : [ { "courseid" : "PHY101", "grade" : "B", "coursename" : "Physics 101", "credits" : 3 }, { "courseid" : "BUS101", "grade" : "B+", "coursename" : "Business 101", "credits" : 3 } ]

ACID transactions What is ACID? Atomicity transactions should function as a single, indivisible unit of work Consistency the database should always move from one consistent state to the next Isolation the results of a transaction are (usually) invisible to other transactions until the transaction is finished Durability once committed, a transaction's changes are permanent

ACID transactions How is ACID represented in MySQL? Atomicity if autocommit=on (default), every statement is committed immediately if not, COMMIT or ROLLBACK should be used explicitly Consistency uses the doublewrite buffer and crash recovery Isolation various isolation levels from which to choose from: RU, RC, RR and S Durability there are many configuration options available for this, among which are: innodb_flush_log_at_trx_commit and sync_binlog

ACID transactions How is ACID represented in MongoDB? Atomicity single document level & no snapshotting for reads Consistency primary = strong secondaries = your choice Isolation not really, but $isolated can help Durability configurable w:majority and/or j:true

CAP theorem CAP theorem was proposed by Eric Allen in 2000 A distributed system can't have the 3 guarantees at the same time. One must be sacrificed

CAP theorem Consistence Availability Partition Tolerant A Anyone will get the same response, data is consistent among instances C P

CAP theorem Consistence Availability Partition Tolerant A System will always respond to requests, no downtime. C P

CAP theorem Consistence Availability Partition Tolerant A System can handle errors (network, hardware failure) C P

CAP theorem A Relational Databases MySQL Postgres Cassandra Riaki C P MongoDB Redis

Data Storage and Data Retrieval MySQL has predefined table definitions Each column can have one (and only one) data type assigned to it There are some limits imposed: columns: 4096 row length: 64 Kb these can change depending on which storage engine is used SQL is a declarative language We can tell MySQL what we want, without worrying about how it is looked for From the application side, there are connectors available for communicating with the server https://www.mysql.com/products/connector/

Data Storage and Data Retrieval Unlike MySQL, MongoDB doesn't have a predefined schema but it does use declarative query language. Documents can have different fields with different data types, for example {x : 1, y : ['test']} and {x : 'percona', y : ISODate('2018-01-01')} are both valid MongoDB documents for the same collection.

Data Storage and Data Retrieval MongoDB doesn't use 3rd form normalization but MySQL does. All documents must contain as much information as possible. There are no joins, only linked documents. Max document size is 16 MB.

Comparing topologies Replica-sets Clusters and shards Master Slave

Scalability What is scalability? "the ability to add capacity by adding resources" Scale up (a.k.a.: vertically) improve hardware resources Scale out (a.k.a.: horizontally) add more nodes

Scalability MongoDB: uses shards to scale writes uses secondaries to scale reads MySQL: can use partitioning and sharding to scale writes (but it's not easy to implement) uses slaves to scale reads

MongoDB and MySQL similarities

How similar is MongoDB to MySQL But these databases are not completely different They share: Security Indexing Multi-user access Concurrency

How similar is MongoDB to MySQL Database terms and concept mapping MySQL MongoDB Database Table Row Column Database Collection Document Key

How similar is MongoDB to MySQL Security: Granular security level User roles Different storage engines: Both mongodb and MySQL share the idea of pluggable storage engine MongoDB engines are: WiredTiger, MMAPv1, InMemory, RocksDB MySQL engines are: InnoDB, MyISAM, MyRocks, Memory, and many more

Query Language

Query Language We will compare mongo SQL and mysql SQL languages briefly and we'll see simple workflow for both: create schema create table insert into table select from table update and delete select with join (mysql only)

Query Language - MySQL

Query Language - MySQL

SQL Definition https://dev.mysql.com/doc/refman/5.7/en/select.html

MongoDB Query Language

"NoSQL" Query Language NoSQL CQL Graph Javascript

Security

Security Both databases feature user and roles as well as enhanced security such as LDAP integration, certificates, and audits Percona Server for MongoDB and Percona Server for MySQL do offer entreprise-grade authentication plugins for free

Security - MongoDB MongoDB has roles since version 2.4 Currently we can set collection at table level granularity LDAP is only available on MongoDB Enterprise but Percona server comes with this plugin free of charge. Audit plugin

Security - MySQL Roles will be available on version 8.0+ We can set permission at database and table-level granularity Grants can be further refined into more atomic privileges CREATE SELECT INSERT UPDATE... MySQL Enterprise functionality (provided to some extent by Percona Server): LDAP authentication Encryption Audit

Performance comparison

Performance There is no way to compare both performance. Each database has its own features and some are faster than others. As a document oriented database MongoDB doesn't a predefined schema and neither a relationship among collections which makes finds really fast (when reading only one document) For example: If using lookups in mongodb the query can be very slow. In the other hand, mysql does that with majesty as it is design to work with tables and conjunctions...

Performance Generic concepts to keep best performance Create indexes (not for all the fields) Split or purge data to keep the database small Be precise on your query (avoid reading unnecessary documents, columns) Use fast disks when the working set doesn't fit in RAM More cores means more parallel job and so on...

Best usage cases

Best Use case There is no right nor wrong answer here although mongodb tend to be more used in application that doesn't require transactions (as its nature) mysql are often used when ACID is required. https://www.percona.com/about-percona/customers https://www.percona.com/about-percona/case-studies

Q&A

Q&A

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