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Presented on November 22, 2014 @ SQLSaturday #350 in Winnipeg, MB Canada
Graph databases are used to represent graph structures with nodes, edges and properties. Neo4j, an open-source graph database is reliable and fast for managing and querying highly connected data. Will explore how to install and configure, create nodes and relationships, query with the Cypher Query Language, importing data and using Neo4j in concert with SQL Server... Providing answers and insight with visual diagrams about connected data that you have in your SQL Server Databases!
Session Level: Intermediate
What's New in Oracle SQL Developer for 2018Jeff Smith
All of the new features in versions 18.1, 18.2, and 18.3 of Oracle SQL Developer.
Some of these slides have animated GIFs - please see the embedded video for a live presentation of these slides.
Graph Databases for SQL Server Professionals - SQLSaturday #350 WinnipegStéphane Fréchette
Presented on November 22, 2014 @ SQLSaturday #350 in Winnipeg, MB Canada
Graph databases are used to represent graph structures with nodes, edges and properties. Neo4j, an open-source graph database is reliable and fast for managing and querying highly connected data. Will explore how to install and configure, create nodes and relationships, query with the Cypher Query Language, importing data and using Neo4j in concert with SQL Server... Providing answers and insight with visual diagrams about connected data that you have in your SQL Server Databases!
Session Level: Intermediate
What's New in Oracle SQL Developer for 2018Jeff Smith
All of the new features in versions 18.1, 18.2, and 18.3 of Oracle SQL Developer.
Some of these slides have animated GIFs - please see the embedded video for a live presentation of these slides.
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We will addresses some critical aspects when RDFying XSD/XML data focusing on the strategy followed when mapping controlled vocabularies expressed in XML enumerations; when dealing with certain unstructured data (those where input strings may generate relevant instances); and when addressing identity resolution and linking tasks once the eventual instances are RDFied. Here we will also report on data cleansing, a crucial and unavoidable task which we addressed as an incremental process where SPARQL played an important role. We will see that some of the decisions taken depend on the eventual application we have in mind. The requirements of our Catalog (implemented as a web browser) include: displaying data to the user in a comprehensive way; aggregating external data in a sensitive manner and making hidden implicit relations explicit. In addition, the system needs to provide fresh data (regularly updated) in a quick response time.
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Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Large Language Model (LLM) and it’s Geospatial Applications
OrientDB: a Document-Graph Database ready for the Cloud - Dell'Aquila
1. ROME 11-12 april 2014ROME 11-12 april 2014
OrientDB: a Document-Graph Database
ready for the Cloud
OrientDB Committer
OrientDB Academy Coordinator at Orient Technologies LTD
Project Manager at AssetData S.r.l.
Email: l.dellaquila – at – orientechnologies.com
Twitter: @ldellaquila
Luigi Dell’Aquila
2. ROME 11-12 april 2014 - Luigi Dell’Aquila
Relational Databases:
Everybody knows what a TABLE is
Everybody knows SQL
3. ROME 11-12 april 2014 - Luigi Dell’Aquila
These are tables,
Data ARE Tables!
4. ROME 11-12 april 2014 - Luigi Dell’Aquila
These are tables,
Data ARE Tables!
5. ROME 11-12 april 2014 - Luigi Dell’Aquila
These are tables,
Data ARE Tables!
20. ROME 11-12 april 2014 - Luigi Dell’Aquila
Two data models:
Graph
and
Document
21. ROME 11-12 april 2014 - Luigi Dell’Aquila
Classes, not Tables
create class Person
create class Student extends Person
select from Person
Polymorphic query: returns both instances of Person and
Student
22. ROME 11-12 april 2014 - Luigi Dell’Aquila
Dynamic schema
create class Person
insert into Person (name, surname) values (“Luigi”,
“Dell’Aquila”)
No need to fully specify the class structure, you can work in
schemaless mode
23. ROME 11-12 april 2014 - Luigi Dell’Aquila
Complex attributes
Update person
set address = {
“street”: “5th Ave”,
“city”: “NY”
},
tags = [“developer”, “artist”, “geek”]
Collections and embedded properties
24. ROME 11-12 april 2014 - Luigi Dell’Aquila
Physical links
(no Join!)
Update person set address.city =
(select from city where name = ‘Rome’)
where name = ‘Luigi’
Select address.city.country.name
from Person where name = ‘Luigi’
Dot notation instead of Join
No need for foreign keys
O(1) computational cost – compared to O(log N) in relational Join
25. ROME 11-12 april 2014 - Luigi Dell’Aquila
The Graph API
(TinkerPop Blueprints)
Traverse out(“Friend”) from
(select from Person where name = ‘Luigi’)
while address.city = ‘Rome’
Find my friends network in my city (friends, firends of frineds,
friends of friends of friends…)
Deep traversal, no need to know in advance HOW deep
26. ROME 11-12 april 2014 - Luigi Dell’Aquila
Every record has unique ID
Select from Person
{"result": [
{
"@rid": "#13:0",
"@class": “Person",
"name": "Luigi",
"surname": "Dell'Aquila",
"friendOf": "#13:1"
}
]}
27. ROME 11-12 april 2014 - Luigi Dell’Aquila
Every record has unique ID
Select from Person
{"result": [
{
"@rid": "#13:0",
"@class": “Person",
"name": "Luigi",
"surname": "Dell'Aquila",
"friendOf": "#13:1"
}
]}
28. ROME 11-12 april 2014 - Luigi Dell’Aquila
Every record has unique ID
Select from Person
{"result": [
{
"@rid": "#13:0",
"@class": “Person",
"name": "Luigi",
"surname": "Dell'Aquila",
"friendOf": "#13:1"
}
]}
29. ROME 11-12 april 2014 - Luigi Dell’Aquila
Record ID (RID)
=
Physical position
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Traversing relationships
=
Following a physical path
31. ROME 11-12 april 2014 - Luigi Dell’Aquila
It means:
• Accessing linked data is very efficient
• No calculation *
• Independent from cluster size **
• Deep traversal is allowed and encouraged ***
* In RDMS, a Join is calculated EVERY TIME you execute a query
** RDBS use index-based optimization to speed up joins, but index
access is O(log N), so it depends on data size – what about Big
Data???
*** in RDMS multiple joins are inefficient (would you dare to write a
query with 1000 joins?)
32. ROME 11-12 april 2014 - Luigi Dell’Aquila
But OrientDB
Gives you more!
33. ROME 11-12 april 2014 - Luigi Dell’Aquila
Javascript In the Storage
Extend the query language
With you own functions
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Javascript functions
As REST services
35. ROME 11-12 april 2014 - Luigi Dell’Aquila
But of course you can use it
from
36. ROME 11-12 april 2014 - Luigi Dell’Aquila
90’s are gone
Today you need