Guacamole Fiesta: What do avocados and databases have in common?

Copyright © ArangoDB Inc. , 2018
One Engine, one Query Language.
Multiple Data Models.

Copyright © ArangoDB Inc., 2018
Guacamole Fiesta
Welcome to our first ArangoDB
meetup in Cologne

Copyright © ArangoDB Inc., 2018 3
Company at a Glance
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10,000s of Users
300+ Production usages
Fortune 10 and 500 customers
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Our mission:
Improve the productivity of every
developer on earth

Product Positioning
RelationshipComplexity
Data Complexity
5
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Key Value

Revenue generating and mission critical
Use Cases Selection
6
Security & Fraud
Detection
Product & Asset
Catalogue
Real-Time
Analytics
Customer and
Content Mgmt
Single View of
Everything
Recommendation
& Commerce
Bitcoin &
Blockchain
IoT and Edge
Computing
Machine Learning
and AI

Performance RocksDB
‣ we constantly improve the performance
‣ in 3.3.9 some use-case are up-to 4x faster
Operational Improvements
‣ parallel Dump & Restore
‣ automatic pacing for Import
‣ AQL query profiling
‣ AQL query debugging
Cluster Optimizations
‣ reduce locking
‣ single shard operations
‣ distributed AQL collect
‣ streaming cursors
Roadmap
New Geo Functions
‣ support for Polygons and Lines
‣ Google’s S2geometry library
ArangoSearch
‣ Comparable to Lucene / Elastic
‣ First version for Single Server available
Others
‣ UPSERT / REPSERT

Download Enterprise Edition (or you can use
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query techniques in AQL – the ArangoDB query
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Multi-Model Database
Movement

The Single Model era is over

The Multi Model era begins
● Map unique string keys => value
● Data is opaque (no schema)
● Easy scaling and partitioning
● Typically based on key => value store
● Save similar documents in collections
● Data Records: Attribute-structured docs
● Index & Query over attributes
● Stores vertices and edges
● Focus: n-to-m relations between vertices
● Vertices and edges have attributes
● Query paths of variable length
● Search for patterns

Use-Case: The Avocado Company
1. We have a company that growths Avocados on a farm, harvests and sales them
2. In this company we have several teams:
a. Teams Clifton, Gordo, Orco & Reed: plant and harvest Avocados of their type
b. Team Marketing: make Avocados even more shiny and tasty
c. Team Bacon: maintain the heavy farming equipment
d. Team Support: Assure quality and help customers with ripening Avocados
e. Team Sales: Bring the best Avocados to the Market
f. Team Management: Take the hard-cored decissions, keep the company running
3. Each team has it’s own territory and access to tools or land, we need to make sure that
no team steals these so everything can growth smoothly

The Data-Model: Relational

The Data-Model: Polyglot
Company & Access Rights
Employee Employee
Team Team
Team Team
Team
Employee
Customer InformationFarm Resources
Field Field Field
Machine Machine
Depot
CID
Info
CID
Info
CID
Info
SALE
BILL
SALE
BILL
SALE
BILL

The Data-Model: Multi-Model
Employee Employee
Team Team
Team Team
Team
Employee
Field Field Field
Machine Machine
Depot
CID
Info
CID
Info
CID
Info
SALE
BILL
SALE
BILL
SALE
BILL

Benefits
► Natural Mapping Application ⇔ DB
► DB optimized for this format
► Format specific queries
► Focus on business logic
► Data redundancy
► Across systems
► Syncing issues
► Several technologies involved
► Learn/master more
► Updating very frequently
► Administration effort
Overhead&

Combine Data Models
Employee Employee
Team Team
Team Team
Team
Employee
Field Field Field
Machine Machine
Depot
CID
Info
CID
Info
CID
Info
SALE
BILL
SALE
BILL
SALE
BILL

ArangoDB feature list
► Native Multi-Model
► AQL (Complex queries, joins and traversals)
► ACID incl. Multi Collection Transactions
► Foxx (extend the API)
► Cluster
► Multi-Master
► DC-2-DC

DEMO TIME

How many Avocados are growing?
FOR field IN Fields
COLLECT AGGREGATE growing = SUM(fields.fruits)
RETURN growing

Who is member of the farmers Team?
FOR team IN Teams
FILTER team.name == "Farmers"
FOR employee IN 1..100 INBOUND team IsPartOf
FILTER IS_SAME_COLLECTION(Employees, employee)
RETURN employee

Do i have access to this field?
FOR me IN Employees
FILTER me._key == "michael"
LET p = (
FOR v IN OUTBOUND
SHORTEST_PATH me TO "Fields/field7" IsPartOf, FarmsOn
LIMIT 1
RETURN 1
)
RETURN p[0] == 1 ? true : false

Which recent deals have been closed?
FOR team IN Teams
FILTER team.name == "Sales"
FOR deal, closed IN 2 INBOUND team IsPartOf, OUTBOUND HasClosed
FILTER closed.date >= "2018-01-01"
RETURN deal

Benefits
► Natural Mapping Application ⇔ DB
► DB optimized for this format
► Format specific queries
► Focus on business logic
► No undesired redundancy
► Only one technology involved
► Learn/master only one DB
► Only keep this updated
► Switch data-model if needed
► More data-model choices
► Afraid to not pick the right one(s)
► (You are not locked-in!)
► A lot to learn on one database
► (Start with one model at a time)
Overhead&

Benchmark Comparison

Foxx

Micro-Service Framework
► Add REST-API to ArangoDB
► Written in JavaScript
► Many node modules available (not all)
► Generate interactive Documentation (Swagger)

► Operations directly inside the database
► Reduce network traffic
► Direct data access
► Complex rights management
► Increase data privacy
► Attribute level access rights
► Multiple dependent queries
Benefits

► Microservice architectures
► The database is "just" a storage micro service
► No query language creeping
► API / data-format migration
► Can deploy different API versions
► "On the fly" document migration
► And many more...
Use-Cases

Foxx Example: members of Team
router.get("/members/:team", function (req, res) {
let query = `FOR team IN Teams FILTER team.name == @team
FOR employee IN 1..100 INBOUND team IsPartOf
FILTER IS_SAME_COLLECTION(Employees, employee)
RETURN employee`;
let result = db._query(query, {team: req.params("team")}).toArray();
res.json(result);
});

Scaling: Sharding
► Used for: Large Dataset and Write-Scaling
► Collection: Distributed in parts (shards) across several servers
► Distributed by: List of User-defined attributes (default: _key)
► Number of Shards is immutable
► Define it upfront
► Each collection can have it's own number of shards
► A collection can at most be distributed to #shards many servers

Scaling: Replication
► Used for: High-Availability
► Every shard has n followers
► Followers:
► Do not accept writes
► Replication is synchronous
► Placed on different physical machines
► On server-failure:
► A follower will take over as leader
► A new follower will be created
► If old leader returns he will be used as new follower

Thank you very much.
Any questions?
Please star:
https://github.com/arangodb/arangodb
Twitter: @arangodb

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