Grab is one of the most frequently used mobile platforms in Southeast Asia, providing the everyday services that matter most to consumers. Its users commute, eat, arrange shopping deliveries, and pay with one e-wallet. Grab relies on the combination of Apache Kafka and Scylla for a very critical use case -- instantaneously detecting fraudulent transactions that might occur across approximately more than six million on-demand rides per day taking place in eight countries across Southeast Asia. Doing this successfully requires many things to happen in near-real time. Join our webinar for this fascinating real-time big data use case, and learn the steps Grab took to optimize their fraud detection systems using the Scylla NoSQL database along with Apache Kafka.

1. Real-Time Fraud
Detection at Grab
Aravind Velamur Srinivasan
Engineering Lead, Grab Technology Corp

2. 2
+ The Real-Time Big Data Database
+ Drop-in replacement for Cassandra
+ 10X the performance & consistent, low latency
+ Open source and enterprise editions
+ New: Scylla Cloud, DBaaS
+ Founded by the creators of KVM hypervisor
+ HQs: Palo Alto, CA; Herzelia, Israel
About ScyllaDB

3. + Engineering Lead at Grab Technologies
+ Streaming Platform
+ Data Platform Infrastructure
+ Worked at Uber Inc prior to Grab
+ Prior to that worked for Isilon/EMC (now DELL)
+ Masters in Computer Science from University of Virginia (UVa)
+ Contact: aravindvelamur@gmail.com
Presenter

4. Background
Overview of TechStack at Grab
Streaming Ecosystem at Grab
Why ScyllaDB
ScyllaDB use at Grab (Fraud Detection)
Conclusion
Q&A
Agenda

5. Background

6. Introduction to Grab
+ One of the most frequently used mobile
platforms in Southeast Asia
+ Multiple services (multi-million users
per day and growing!)
+ Transport
+ Food
+ Payment
+ Shopping
+ Package Delivery
+ ...

7. Tech Stack Overview

8. Tech Stack at Grab
+ Backend Services
+ Golang
+ More than 100s of services
+ Inter-Service Communication
+ protobuf/gRPC (for the most part)

9. Tech Stack at Grab

10. Streaming Ecosystem
at Grab

11. Streaming Ecosystem at Grab

12. Streaming Ecosystem at Grab
Service A
Service C
Service D
Service G
Service F
Service E
Service H
Service B

13. Why ScyllaDB

14. Why ScyllaDB

15. Why ScyllaDB
+ Recap of Grab Tech

16. Why ScyllaDB
+ Recap of Grab Tech
+ Microservices (Golang)

17. Why ScyllaDB
+ Recap of Grab Tech
+ Microservices (Golang)
+ Kafka for streaming

18. Why ScyllaDB
+ Recap of Grab Tech
+ Microservices (Golang)
+ Kafka for streaming
+ Why? Loose coupling and Scale! doh! :)

19. Why ScyllaDB
➔ Stream Processing
➔ Transforms
➔ Aggregates
➔ Joins
➔ ...

20. Why ScyllaDB
+ Required a State store (metadata store) which has the following
characteristics:
+ Ability to handle very high throughput
+ Ability to handle bursts (doh!)
+ Ability to scale out (i.e, handle hockey stick like growth)
+ Very low latencies (both write and reads) - Near Real-Time
+ Low operational overhead
+ Cost efficient

21. Why ScyllaDB

22. ScyllaDB USAGE

23. ScyllaDB Usage
Use Cases

24. ScyllaDB Usage
Low Latency
Use Cases

25. ScyllaDB Usage
Low Latency
High
Throughput
Use Cases

26. ScyllaDB Usage
Low Latency
High
Throughput
Easy Scale
Use Cases

27. ScyllaDB Usage
Low Latency
High
Throughput
Easy Scale Build Stats
Use Cases

28. Number of Use cases revolving around:
+ Stream Aggregation &
+ For Eg:- Fraud Detection in Real-Time
+ Stream Statistics
+ ...
ScyllaDB Usage

29. RT Fraud Detection

30. + Why? Eg: Fraud Detection
https://www.scmp.com/week-asia/business/article/2154770/who-pays-when-indonesian-ride-sharing-fraud-goes-full-throttle
https://www.techrepublic.com/article/seven-ride-sharing-scams-to-watch-out-for/
+ Grab’s own Blog:
https://www.grab.com/sg/blog/why-anti-fraud-technology-is-the-secret-sauce-to-winning-ride-hailing-platforms/
ScyllaDB Usage - Fraud Detection

31. + Why? Eg:- Fraud Detection
ScyllaDB Usage - Fraud Detection
...
The big influx of capital into the industry has led to fraudsters, sometimes individuals,
sometimes organised in gangs, trying to game incentive and sign-up schemes. As a
result, a stolen ride-hailing driver profile today is worth up to US$30 on the black market,
even more than stolen credit card information.
…

32. ScyllaDB Usage - Why Fraud Detection?

33. + Use Kafka streams to do real-time Fraud detection
+ Simple Use Case:
+ Some scammers use fake GPS to say they are online at multiple locations
ScyllaDB Usage - Fraud Detection

34. + Simple Use case:
ScyllaDB Usage - Fraud Detection
Grab
Service
GPS
driver_location topic
Fraud
Detection
Service
Algorithm

35. + Complex Use Case:
+ Fraudsters evolve :)
+ Consuming one topic is not enough
+ Example:
ScyllaDB Usage - Fraud Detection
Use fake GPS tools and modded phones to simulate driving
behaviour and completed rides to game the system.

36. ScyllaDB Usage - Fraud Detection
Topic 1
Stream
Processing
Engine
Grab Service(s)
Grab Service(s)
Grab Service(s)
Topic 2
Topic 3
Combined
Topic
Fraud
Detection
Service
Algorithm

37. + In summary using ScyllaDB
+ Joined multiple Kafka streams together in Real-Time!!
+ Like joining SQL tables together!
ScyllaDB Usage - Fraud Detection

38. ScyllaDB Other Usages

39. ScyllaDB Usage - Stream Statistics

40. + Teams like to find out:
+ Counts of … (eg: count of rides in the past month, etc)
+ Raw stats for a particular key
+ Business users - require stats on city/country data
ScyllaDB Usage - Stream Statistics

41. ScyllaDB Usage - Stream Statistics
+ Requires a fast store for raw stats
+ Ability to build Time series on top of it.

42. Conclusion

43. ScyllaDB at Grab So Far...
Overall
+ Great experience
+ Cost effective
+ Very responsive team
+ As good as advertised :)
+ Growing within the company…

44. ScyllaDB at Grab So Far...
+ Some hiccups
+ nodetool repair - Writes and read timeouts every time when the run finishes
(even with -pr)
+ Wish nodes can join the cluster faster
+ Right now takes a really long time (approx 1TB data on each node across all
keyspaces) - takes ~2.5 hours to add a node
+ Understand why but can we design something asynchronous?
+ Better error logging

45. Q&A
Stay in touch
aravindvelamur@gmail.com
Thank you
United States
1900 Embarcadero Road
Palo Alto, CA 94303
Israel
11 Galgalei Haplada
Herzelia, Israel
www.scylladb.com
@scylladb