The document discusses effectively evaluating data solutions for systems. It recommends identifying the business value and needs, such as scale and future costs. It also suggests analyzing expected performance by considering the solution's purpose, resource requirements, and resilience. Additionally, it advises overseeing future plans like the system's scale support, R&D growth plan, and learning curve. The overall document provides guidance on comprehensively evaluating data solutions by examining business value, performance, and future oversight.

1. One Size Doesn’t Fit All
Effectively (Re)Evaluate a
data solution for your
system

2. Hi 👋
Eynav Mass
VP R&D at Oribi
And a happy mother :)

3. Let’s talk about...
How to effectively
evaluate a data solution
for your system
💡

4. Let’s talk about - evaluating data solutions
Why bother?
🤔

5. Let’s talk about - evaluating data solutions

6. Let’s talk about - evaluating data solutions

7. Let’s talk about - evaluating data solutions

8. Case Study

9. is about:
Codeless Data

10. is about:
Codeless Data Insights and
Visualization

11. is about:
Codeless Data Insights and
Visualization
Export Data
Check out our site for more info: oribi.io

12. : A BIG-DATA based product
300,000,000 incoming events a day
Auto-Scaled µ-service based architecture
Optimized infrastructure

13. 300,000,000 incoming events a day
Auto-Scaled µ-service based architecture
Optimized infrastructure
: A BIG-DATA based product

14. 300,000,000 incoming events a day
Auto-Scaled µ-service based architecture
Optimized infrastructure
: A BIG-DATA based product

15. From POC to Production

16. From POC to Production

17. From POC to Production
300,000,000 incoming events a day
POC for a new feature at Oribi
PostgreSQL with heavy computation

18. From POC to Production
300,000,000 incoming events a day
POC for a new feature at Oribi
PostgreSQL with heavy computation
Multiple writes Heavy Read Traffic Scale
+ =

19. From POC to Production
300,000,000 incoming events a day
POC for a new feature at Oribi
PostgreSQL with heavy computation
💯 Velocity ⛔️ Performance

21. ○ Resources
○ Knowledge / Experience
○ Time
○ Over Motivated Developers :)
○ ...
Reality Check :
Why do we have “non-optimized” data solutions

22. Let’s talk about - evaluating data solutions Effectively

23. 🎯 Business value
🚀 Performance
⚗️ Overseeing Future Plans
Let’s talk about - evaluating data solutions Effectively

24. 🎯 Business value
🚀 Performance
⚗️ Overseeing Future Plans
Let’s talk about - evaluating data solutions Effectively

25. Identify the business value and needs

26. Identify the business value and needs: Scale
Scale

27. Identify the business value and needs: Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale
Scale

28. Identify the business value and needs: Scale
Customer Base

29. Identify the business value and needs: Scale
Usage
Customer Base

30. Identify the business value and needs: Scale
Usage
3x Scale of active users

31. Identify the business value and needs: Scale
Ingestion Services

32. Identify the business value and needs: Scale
Ingestion Services

33. Identify the business value and needs: Scale

34. Identify the business value and needs
➢ Scale
➢ Go To Market
➢ Product Requirements
➢ Future Costs

35. 🎯 Business value
🚀 Performance
⚗️ Overseeing Future Plans
Let’s talk about - evaluating data solutions Effectively

36. Analyze the expected performance

37. Analyze the expected performance

38. Analyze the expected performance
“It worked on the POC...”
“It worked on the staging...”
“It works great on my local...”

39. Analyze the expected performance
➢ What will be the main purpose of the solution ?

40. Analyze the expected performance
➢ What will be the main purpose of the solution ?

41. Analyze the expected performance
➢ What will be the main purpose of the solution ?
➢ Where will be the heavy load? Write | Update | Read?

42. Analyze the expected performance
➢ What will be the main purpose of the solution ?
➢ Where will be the heavy load? Write | Update | Read?
➢ Which types of resource will be needed?

43. Analyze the expected performance
➢ What will be the main purpose of the solution ?
➢ Where will be the heavy load? Write | Update | Read?
➢ Which types of resource will be needed?
CPU Mem

44. Analyze the expected performance
➢ What will be the main purpose of the solution ?
➢ Where will be the heavy load? Write | Update | Read?
➢ Which types of resource will be needed?
CPU Mem I/O Network Storage Concurrency

45. Analyze the expected performance
➢ What will be the main purpose of the solution ?
➢ Where will be the heavy load? Write | Update | Read?
➢ Which types of resource will be needed?
➢ Resilience and high availability

46. Analyze the expected performance
➢ What will be the main purpose of the solution ?
➢ Where will be the heavy load? Write | Update | Read?
➢ Which types of resource will be needed?
➢ Resilience and high availability
Recovery Methods Zero Downtime

47. Analyze the expected performance
➢ What will be the main purpose of the solution ?
➢ Where will be the heavy load? Write | Update | Read?
➢ Which types of resource will be needed?
➢ Resilience and high availability
➢ Observability; the ability to monitor 360o

48. 🎯 Business value
🚀 Performance
⚗️ Overseeing Future Plans
Let’s talk about - evaluating data solutions Effectively

49. Overseeing Future Plans :
Online Analytics System Development in Alibaba

50. Overseeing Future Plans :
Online Analytics System Development in Alibaba

51. Overseeing Future Plans :
Online Analytics System Development in Alibaba

52. Overseeing Future Plans :
Online Analytics System Development in Alibaba

53. Overseeing Future Plans
➢ The plans for the system, scale support, technologies

54. Overseeing Future Plans
➢ The plans for the system, scale support, technologies
➢ The R&D growth plan

55. Overseeing Future Plans
➢ The plans for the system, scale support, technologies
➢ The R&D growth plan
➢ Learning curve
Oracle HBase + Hadoop

56. Overseeing Future Plans
➢ The plans for the system, scale support, technologies
➢ The R&D growth plan
➢ Learning curve
➢ Can the solution enrich other features? 1+1 =3

57. Overseeing Future Plans
➢ The plans for the system, scale support, technologies
➢ The R&D growth plan
➢ Learning curve
➢ Can the solution enrich other features? 1+1 =3

58. 🎯 Business value
🚀 Performance
⚗️ Overseeing Future Plans
Let’s talk about - evaluating data solutions Effectively

59. THANK YOU
https://www.linkedin.com/in/eynavmass