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The open-source database
for the realtime web
Aleksandr Ivanov, @4lex1v
Cake Solutions, L&L, 2 October 2015
The open-source database
First commit: 4 October 2009
Latest release: RethinkDB 2.1 (Forbidden Planet)
Github Stars: 10453
Commits: ~ 32k commits, 15-20 active contributors
The open-source database
• NoSQL storage for your lovely schemaless JSON documents!
• Distributed solution that is easy to scale
• Simplifies the development of realtime web apps
• And there is even more!
The open-source database
• More and more apps are built to be realtime
• Users want to interact with the application in realtime
• In many applications are expected to work in realtime
The realtime web
• Scalability vs Complexity
• State management
The realtime web is
HARD
• Keep everything on a single machine
• Polling database for an updates (hello Mongo oplogs)
• Use message brokers / commit logs to publish updates
The realtime web is
HARD
• Changefeeds - subscribing to change notifications from the code
• No more polling and brokers - RethinkDB pushes changes to your app
• Live streaming out of the box!
RethinkDB - Push
Database
• Collaborative web and mobile applications
• Multiplayer games
• Live streaming, monitoring and analytics
• Connected devices
RethinkDB - Push
Database
RethinkDB Query
Language
Official Drivers:
• Node.js
• Python
• Ruby
• Java (in progress)
RethinkDB Query
Language
• ReQL embeds natively into the language
• Queries compose naturally by chaining
• Queries are executed lazily on the server
RethinkDB Query
Language
r.table(“users”).filter(_.age > 36)
r.table(“users”)
.pluck(“last_name”)
.distinct().count()
r.table(“fellowship”)
.filter(_.species == “hobbit”)
.update(_.species -> “halfling”)
RethinkDB Query
Language
Transformations: map, orderBy, skip, limit, slice, etc…
Aggregations: group, reduce, count, sum, distinct, contains, etc…
Documents: pluck, merge, diff, keys, without, etc…
Writes: insert, update, replace, delete
Control: forEach, range, branch, do, expr, coerceTo, etc…
Joins: innerJoin, outerJoin, eqJoin, zip
RethinkDB Data
Modeling
There are two ways to model relationships between documents:
• By using embedded arrays.
• By linking documents stored in multiple tables
RethinkDB Data
Modeling
# authors table
{
id: 123,
name: “Aleksandr”,
talks: [
{ title: “Introduction to RethinkDB” },
{ title: “Scala, the Modular Language” }
]
}
RethinkDB Data
Modeling
# Retrieve all authors with their talks
r.db("blog").table("authors")
# Retrieve a single author with his talks
r.db("blog").table("authors").get(ID)
RethinkDB Data
Modeling
# authors table
{
id: 123
name: “Aleksandr”
}
RethinkDB Data
Modeling
# talks table
{
id: 1,
authors_id: 123,
title: “Introduction to RethinkDB”
},
{
id: 2,
authors_id: 123,
title: “Scala, the Modular Language”
}
RethinkDB Data
Modeling
# Simple query using filter
r.db(“blog").table("talks")
.filter(_.authors_id == 123)
# Match results from different tables
# with Join operation and secondary index
r.table(“authors”)
.getAll(“Aleksandr”, “authors”)
.eqJoin(“id”, r.table(“talks”), “authors”)
RethinkDB Data
Modeling
Embedded arrays vs multiple tables ???
Data modeling - http://www.rethinkdb.com/docs/data-modeling/
Table Joins - http://www.rethinkdb.com/docs/table-joins/
RethinkDB
Changefeeds
Subscribe to change notifications on database queries
r.table(“users”).changes()
Track changes of the users table
RethinkDB
Changefeeds
• The changes command creates a cursor that receives updates
• Each incoming notification includes the new and old
value of the modified record
RethinkDB
Changefeeds
r.table(“users”).changes()
r.table(“users”).insert(User(“Aleksandr”))
{
new_val: { id: “123”, name: “Aleksandr” },
old_val: null
}
Changefeed output:
RethinkDB
Changefeeds
r.table(“users”).changes()
r.table(“users”).get(“123”)
.update(_.name -> “Sasha”)
{
new_val: { id: “123”, name: “Sasha” },
old_val: { id: “123”, name: “Aleksandr” }
}
Changefeed output:
RethinkDB
Changefeeds
r.table(“users”).changes()
r.table(“users”).filter(_.name == “Sasha”).delete()
{
new_val: null,
old_val: { id: “123”, name: “Sasha” }
}
Changefeed output:
RethinkDB
Changefeeds
r.table(“users”)
.filter(_.likes >= 30)
.changes()
Get notifications when a user gets over 30 likes:
Clients can subscribe to the realtime stream of updates
Advanced realtime
web
• Polling date is slow, cumbersome and hard to maintain
• The push access model simplifies realtime architecture
• Single source of truth makes it easy to maintain state

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