SpringOne 2020 Nikhil Chandrappa: Software Engineer Lead, Yugabyte Inc; Anthony Vetter: Sr. Product Marketing Manager, VMware

1. © 2020 - All Rights Reserved 1
Cloud-Native Spring
Microservices with
Distributed SQL Backend
on Kubernetes
Nikhil Chandrappa
Lead Software Engineer
Yugabyte
Tony Vetter
Sr. Product Marketing Manager
VMware

2. Disclaimer
● This presentation may contain product features or functionality that are currently under
development.
● This overview of new technology represents no commitment from Yugabyte to deliver these
features in any generally available product.
● Features are subject to change, and must not be included in contracts, purchase orders, or sales
agreements of any kind.
● Technical feasibility and market demand will affect final delivery.
● Pricing and packaging for any new features/functionality/technology discussed or presented, have
not been determined.
● The information in this presentation is for informational purposes only and may not be incorporated
into any contract. There is no commitment or obligation to deliver any items presented herein.

3. Cloud-Native era: Database decisions
NoSQL or SQL?
How do I Scale? More Apps
(Microservices)
Move to Private/Public Cloud
Traditional DBs
3

4. Databases for Cloud – the hard problem!

5. Cloud-Native era: Scale and Resiliency
●
●
●
●

6. What is Distributed SQL?
SQL &
Transactions
SQL
Massive
Scalability
Geo
Distribution
Ultra Resilience
A Revolutionary Database Architecture

7. Popular Distributed SQL DBs in Public Cloud
Aurora much more popular than Spanner
bit.ly/distributed-sql-deconstructed
Amazon Aurora Google Spanner
A highly available MySQL
and PostgreSQL-compatible
relational database service
Not scalable but HA
All RDBMS features
PostgreSQL & MySQL
The first horizontally scalable,
strongly consistent, relational
database service
Scalable and HA
Missing RDBMS features
New SQL syntax

8. Google Spanner - Paxos
Ref: https://cloud.google.com/spanner/docs/whitepapers

9. YugabyteDB - Raft Consensus
node1 node2 node3 node4 … Scale to as many nodes as needed
Raft group leader (serves writes & strong reads)
Raft group follower (serves timeline-consistent reads & ready for leader election)
syscatalog
yb-admin1
YB-Admin Service
Manage shard metadata &
coordinate config changessyscatalog
yb-admin2
syscatalog
yb-admin3
Cluster Administration
Admin clients
…
yb-tserver1
tablet3
tablet2
tablet1
YB-TServer Service
Store & serve app data
in/from tablets (aka shards)
yb-tserver2 yb-tserver3 yb-tserver4
…
tablet4
tablet2
tablet1
…
tablet4
tablet3
tablet1
…
tablet4
tablet3
tablet2
App clients
Distributed SQL API
Distributed
Txn Mgr
Distributed
Txn Mgr
Distributed
Txn Mgr
Distributed
Txn Mgr

10. Scaling out PostgreSQL for multi region
Client
Apps
Client
Apps

11. All Data Nodes are Identical
……
SQL
Query Layer
SQL
Query Layer
SQL
Query Layer
DocDB
Storage Layer
DocDB
Storage Layer
DocDB
Storage Layer
Can connect to ANY node
Add/remove nodes anytime
YugabyteDB Node YugabyteDB Node YugabyteDB Node
API
SQL
Query

12. Spring Framework Support
for distributed SQL
workloads

13. Spring support for Data Ecosystem
Ref: https://spring.io/projects/spring-data

14. Cluster Aware JDBC Driver

15. Cluster Aware JDBC Driver: Scale Up

16. Cluster Scale Up

17. DEMO: Cluster aware
driver

18. Questions?
Join Slack Discussions