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NewSQL and Distributed SQL

Data SystemsDistributed SQLđŸŸĸ Free Lesson

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Data Systems

NewSQL and Distributed SQL

NewSQL databases combine the best of SQL and NoSQL: strong consistency, ACID transactions, and horizontal scalability. Master the architecture of Spanner, CockroachDB, and YugabyteDB.

  • Consistency — Serializable transactions across distributed nodes
  • Scalability — Horizontal scaling with automatic sharding
  • Global — Multi-region deployment with low-latency reads

NewSQL proves you don't have to sacrifice consistency for scalability.

The NewSQL Promise

NewSQL databases aim to provide the scalability of NoSQL with the ACID guarantees and SQL interface of traditional relational databases.

The CAP Theorem in Practice

Traditional SQL+ Strong consistency+ ACID transactions+ SQL interface- Vertical scaling only- Single point of failure- Limited geographic reachNoSQL+ Horizontal scalability+ High availability+ Geographic distribution- Eventual consistency- Limited transactions- No JOINs or SQLNewSQL+ Horizontal scalability+ Strong consistency+ ACID transactions+ SQL interface+ Global distribution~ Higher write latency

Google Spanner

TrueTime and External Consistency

Spanner Architecture

ComponentPurpose
SpanserverStores data, serves queries
Zone MasterAssigns data to spanservers
Directory ManagerMoves data between zones
Placement DriverManages cross-zone replication

CockroachDB

Raft Consensus

LeaderNode 1FollowerNode 2FollowerNode 3FollowerNode 4Append entriesHeartbeat

CockroachDB vs Spanner

FeatureCockroachDBSpanner
ConsensusRaftPaxos
Time SourceHybrid logical clocksTrueTime (atomic clocks)
DeploymentSelf-hosted, cloudGCP only
ConsistencySerializableExternal consistency
LatencyHigher (no atomic clocks)Lower (TrueTime)
CostLowerHigher (GCP pricing)

Distributed SQL Internals

Automatic Sharding

Transaction Coordination

When to Use NewSQL

Use CaseJustification
Global financial systemsStrong consistency across regions
Multi-region applicationsLow-latency reads worldwide
ACID at scaleTransactions across sharded data
Regulatory complianceData residency with consistency
Migration from monolithKeep SQL while gaining scalability

Practice Exercises

  1. Architecture Comparison: Compare Spanner and CockroachDB for a global e-commerce platform. What are the trade-offs in terms of consistency, latency, cost, and operational complexity?

  2. Transaction Design: Design a distributed transaction for a banking system that transfers money between accounts in different regions. How do you handle the coordination?

  3. Sharding Strategy: If you were designing CockroachDB's automatic sharding, what algorithm would you use to distribute data? How do you handle hot spots?

  4. Migration Planning: Your team is migrating from PostgreSQL to CockroachDB. What are the main challenges, and how would you approach the migration?


What to Learn Next

-> Spanner and CockroachDB Deep dive into specific NewSQL implementations.

-> SQL Deep Dive PostgreSQL, MySQL, indexing strategies, and query optimization.

-> Distributed Consensus Paxos, Raft, and consensus protocols.

-> CAP Theorem Consistency models, availability, and partition tolerance.

-> Data Partitioning Sharding strategies, consistent hashing, and partition keys.

-> Data Replication Sync vs async replication, leader election, and consistency.

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