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Relational Databases
Don’t call it a comeback!
Who is this guy?
Rob Hedgpeth
Developer Relations @ MariaDB
robh@mariadb.com
@probablyrealrob
rhedgpeth
How did this...
@probablyrealrob
Data
Database
Become this...
@probablyrealrob
SQL
NoSQL NewSQL
Relational
Non-Relational
Object
Spatial
Key-Value
Graph
Graph
Document
Distributed
OLTP
OLAP Wide-Column
Columnar
HTAP
Clustered
The History of Databases
@probablyrealrob
1960’s 1970’s 1980’s 1990’s 2000’s 2010’s 2020+
Early Databases
@probablyrealrob
Customer
Order
Order-line
Product
Shipment
Network Model
Part
Customer Purchase
Order
Stock
Detail
Hierarchical Model
@probablyrealrob
1960’s 1970’s 1980’s 1990’s 2000’s 2010’s 2020+
Edgar Codd
Yo...check
this out!
Relational Databases
@probablyrealrob
id type description
1 A Item 1
2 B Item 2
3 C Item 3
Rows
Columns
Relational Databases
@probablyrealrob
People
id
name
person_id
address_id
Addresses
id
address
PA
@probablyrealrob
Simplify
Retrieval
Eliminate
Redundancy
Improve
Integrity
Relational Databases
@probablyrealrob
1960’s 1970’s 1980’s 1990’s 2000’s 2010’s 2020+
Edgar Codd
ANSI/ISO
Raymond Boyce Don Chamberlain
Structured Query Language
@probablyrealrob
SQL
@probablyrealrob
SQL Commands
DDL DML DCL TCL
CREATE
ALTER
DROP
TRUNCATE
INSERT
UPDATE
DELETE
GRANT
REVOKE
COMMIT
ROLLBACK
SAVE POINT
DQL
SELECT
SQL Statements
@probablyrealrob
CREATE TABLE tasks (
id INT(11) unsigned NOT NULL AUTO_INCREMENT,
description VARCHAR(200) NOT NULL
PRIMARY KEY (id)
);
INSERT INTO tasks (description)
VALUES (‘Task 1’), (‘Task 2’);
SELECT * FROM tasks WHERE id = 2;
id description
1 Task 1
2 Task 2
@probablyrealrob
1960’s 1970’s 1980’s 1990’s 2000’s 2010’s 2020+
Edgar Codd
Database Management Systems
@probablyrealrob
App
Database
Management
System
(DBMS)
User
App
Database
API
API
API
The Rise of Applications
@probablyrealrob
Size
Complexity
Relational
Comfort Zone
Artificial Intelligence / Machine Learning
@probablyrealrob
Scaling: Vertically
$ $$ $$$
@probablyrealrob
partitioning
Scaling: Horizontally
@probablyrealrob
1960’s 1970’s 1980’s 1990’s 2000’s 2010’s 2020+
Edgar Codd
NoSQL
NoSQL Data Models
@probablyrealrob
Document
Key Value
Key Value
Key Value
Key-Value Graph Column-Family
NoSQL Focus
@probablyrealrob
NoSQL Databases
Scalability Flexibility Availability Performance
NoSQL Purpose
@probablyrealrob
NoSQL
SQL
SQL
SQL
MySQL
MSSQL
Oracle
The Modern Database Landscape
The Relational Resurgence
@probablyrealrob
SQL
@probablyrealrob
Supporting Semi-Structured Data
name format price attr
Aliens Blu-ray -87.7255662 { “resolution”:”1080p”, “aspectRatio”:”1,85:1” }
Relational JSON
Real-Time Analytics with Columnar storage
@probablyrealrob
SELECT AVG(col9) FROM my_tbl
col1 col2 … col9
r1col1 r1col2 r1coln r1col9
r2col2 r2coln r2col9
r3col1 r3col2 r3coln r3col9
r4col1 r4col2 r4coln r4col9
r2col1
col1 col2 … col9
r1col1 r1col2 r1coln r1col9
r2col2 r2coln r2col9
r3col1 r3col2 r3coln r3col9
r4col1 r4col2 r4coln r4col9
r2col1
200 bytes per row, 1B rows
200GB of disk IO
4 byte column, 1B rows
4GB of disk IO
Row-based Column-based
Hybrid Transactional/Analytical Processing
@probablyrealrob
airlines
...
SELECT
a.airline, AVG(f.dep_delay)
FROM
travel.airlines a
INNER JOIN
travel_history.flights f
ON a.iata_code = f.carrier
GROUP BY
a.airline
flights
...
Row-based Column-based
Distributed SQL
@probablyrealrob
Database
Node 1
Database
Node2
Database
Node 3
SQL
Fully distributed data
Distributed SQL
@probablyrealrob
Database
Node
Database
Node
Database
Node
Database
Node
Database
Node
Database
Node
Database
Node
Database
Node
INCOMING
MARIADB PLUG
GO ANYWHERE WITH SKYSQL
Any workload. Any cloud. Any scale.
SkySQL is the first and only DBaaS capable of deploying MariaDB as a:
● Distributed SQL database for scalable transaction processing
● Multi-master cluster for continuous availability
● Multi-node columnar database for data warehousing and analytics
https://mariadb.com/skyview
developers@mariadb.com @mariadb mariadb-corporation
Relational Databases:  Don't call it a comeback!

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Relational Databases: Don't call it a comeback!

Editor's Notes

  1. By the mid-1960s, as computers developed speed and flexibility, and started becoming popular, many kinds of general use database systems became available. As a result, customers demanded a standard be developed, in turn leading to Bachman forming the Database Task Group. This group took responsibility for the design and standardization of a language called Common Business Oriented Language (COBOL). The Database Task Group presented this standard in 1971, which also came to be known as the “CODASYL approach.” The CODASYL approach was a very complicated system and required substantial training. It depended on a “manual” navigation technique using a linked data set, which formed a large network. Searching for records could be accomplished by one of three techniques: Using the primary key (also known as the CALC key) Moving relationships (also called sets) to one record from another Scanning all records in sequential order Eventually, the CODASYL approach lost its popularity as simpler, easier-to-work-with systems came on the market.
  2. By the mid-1960s, as computers developed speed and flexibility, and started becoming popular, many kinds of general use database systems became available. As a result, customers demanded a standard be developed, in turn leading to Bachman forming the Database Task Group. This group took responsibility for the design and standardization of a language called Common Business Oriented Language (COBOL). The Database Task Group presented this standard in 1971, which also came to be known as the “CODASYL approach.” The CODASYL approach was a very complicated system and required substantial training. It depended on a “manual” navigation technique using a linked data set, which formed a large network. Searching for records could be accomplished by one of three techniques: Using the primary key (also known as the CALC key) Moving relationships (also called sets) to one record from another Scanning all records in sequential order Eventually, the CODASYL approach lost its popularity as simpler, easier-to-work-with systems came on the market. The network model is a database model conceived as a flexible way of representing objects and their relationships. Its distinguishing feature is that the schema, viewed as a graph in which object types are nodes and relationship types are arcs, is not restricted to being a hierarchy or lattice. The network model was adopted by the CODASYL Data Base Task Group in 1969 and underwent a major update in 1971. It is sometimes known as the CODASYL model for this reason. A number of network database systems became popular on mainframe and minicomputers through the 1970s before being widely replaced by relational databases in the 1980s. IMS DB is a DBMS that helps you organize business data with both program and device independence. Hierarchical databases and data manipulation language (DL/I calls) are at the heart of IMS DB. Data within the database is arranged in a tree structure, with data at each level of the hierarchy related to, and in some way dependent upon, data at the higher level of the hierarchy. Figure 1 shows the hierarchical database model. In a hierarchical database, data is stored within the database only once. The data item is then available to any user who is authorized to use it. Users do not need to have personal copies of the data.
  3. When people speak of true databases -- they often refer to more structured electronic databases such as relational databases, object databases, OLAP databases, and spatial databases. These kinds of databases can trace their roots back to the 1970 when E.F. Codd from IBM introduced the idea of relational model of databases in his paper entitled "A Relational Model of Data for Large Shared Banks". Before that time most business databases were based on the network model or simple flat file structure. Edgar Codd worked for IBM in the development of hard disk systems, and he was not happy with the lack of a search engine in the CODASYL approach, and the IMS model. He wrote a series of papers, in 1970, outlining novel ways to construct databases. His ideas eventually evolved into a paper titled, A Relational Model of Data for Large Shared Data Banks, which described new method for storing data and processing large databases. Records would not be stored in a free-form list of linked records, as in CODASYL navigational model, but instead used a “table with fixed-length records.” IBM had invested heavily in the IMS model, and wasn’t terribly interested in Codd’s ideas. Fortunately, some people who didn’t work for IBM “were” interested. In 1973, Michael Stonebraker and Eugene Wong (both then at UC Berkeley) made the decision to research relational database systems. The project was called INGRES (Interactive Graphics and Retrieval System), and successfully demonstrated a relational model could be efficient and practical. INGRES worked with a query language known as QUEL, in turn, pressuring IBM to develop SQL in 1974, which was more advanced (SQL became ANSI and OSI standards in 1986 1nd 1987). SQL quickly replaced QUEL as the more functional query language. RDBM Systems were an efficient way to store and process structured data. Then, processing speeds got faster, and “unstructured” data (art, photographs, music, etc.) became much more common place. Unstructured data is both non-relational and schema-less, and Relational Database Management Systems simply were not designed to handle this kind of data.
  4. The main advantage of a relational database is its formally described, tabular structure, from which data can be easily stored, categorized, queried, and filtered without needing to reorganize database tables. Further benefits of relational databases include: Scalability: New data may be added independent of existing records. Simplicity: Complex queries are easy for users to perform with SQL. Data Accuracy: Normalization procedures eliminate design anomalies. Data Integrity: Strong data typing and validity checks ensure accuracy and consistency. Security: Data in tables within a RDBMS can limit access to specific users. Collaboration: Multiple users can access the same database concurrently.
  5. Ray Boyce Don Chamberlain
  6. The SQL programming language was first developed in the 1970s by IBM researchers Raymond Boyce and Donald Chamberlin. The programming language, known then as SEQUEL, was created following the publishing of Edgar Frank Todd's paper, "A Relational Model of Data for Large Shared Data Banks," in 1970. In his paper, Todd proposed that that all data in a database be represented in the form of relations. It was based on this theory that Boyce and Chamberlin came up with SQL. In the book "Oracle Quick Guides (Cornelio Books 2013)," author Malcolm Coxall writes that the original SQL version was designed to manipulate and retrieve data stored in IBM's original relational database management systems known as "System R." It wasn't until several years later, however, that the SQL language was made available publicly. In 1979, a company called Relational Software, which later became Oracle, commercially released its own version of the SQL language called Oracle V2. Since then, the American National Standards Institute (ANSI) and the International Standards Organization have deemed the SQL language the standard language in relational database communication. While major SQL vendors do modify the language to their desires, most base their SQL programs off of the ANSI approved version. The SQL programming language was originally developed on the basis of tuple relational calculus and relational algebra. The major components of this language include the following: Data definition language Data manipulation language Data Control Language. The areas within which SQL programming language can be used include data insertion, update, query, and delete, data access control, and modification and creation of schema. Even though SQL programming language is regarded as a declarative language to a great extent, but it also consists of some procedural elements.
  7. Data Definition Language (DDL) DDL changes the structure of the table like creating a table, deleting a table, altering a table, etc. All the command of DDL are auto-committed that means it permanently save all the changes in the database. Data Query Language DQL is used to fetch the data from the database. Data Manipulation Language (DML) DML commands are used to modify the database. It is responsible for all form of changes in the database. The command of DML is not auto-committed that means it can't permanently save all the changes in the database. They can be rollback. Data Control Language DCL commands are used to grant and take back authority from any database user. Transaction Control Language TCL commands can only use with DML commands like INSERT, DELETE and UPDATE only. These operations are automatically committed in the database that's why they cannot be used while creating tables or dropping them.
  8. Popping up of many database solutions you know of today
  9. https://searchsqlserver.techtarget.com/definition/database-management-system the DBMS essentially serves as an interface between databases and end users or application programs, ensuring that data is consistently organized and remains easily accessible.
  10. Popping up of many database solutions you know of today
  11. Document = Mongo Key-Value = Redis Graph = Neo4j Column-Family = Cassandra
  12. Block = general purpose Sphere = built for a specific purpose
  13. SQL is the second most popular language among developers Due to several factors: SQLite is the most popular relational database in the world due to its use as an embedded database Because SQL is a declarative language it has been modified to handle all kinds of new features, functionality, and data storage techniques.