Cosmos db
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Cosmos DB is a globally distributed, multi-model database as a service. It supports popular database models like document, graph, and key-value and provides high availability, elastic scalability, and tunable consistency. Cosmos DB partitions data across logical replicas for availability and scales throughput globally. It ensures low latency access to data within 10ms and maintains business continuity during regional outages through multiple read regions.
![Cosmos DB - Background
• IaaS – Compute, Storage and Network
• PaaS – Brand of Products – OS, Databases, Middleware as managed service
Management and Sizing is planned by Provider
• SaaS – Readily available Product – SalesForce, Gmail, PeopleSoft, SAP
SuccessFactors
• DBaaS [database-as-a-service]
1. SQL Database – Structured Database as service
2. Azure Document DB – NoSQL Database service with support for Document model
3. Cosmos DB – evolution of Document DB with multi model support
Supported Models – MongoDB, Gremlin, Cassandra, Table /SQL API
ServiceModels](https://image.slidesharecdn.com/cosmosdb-190411030431/85/Cosmos-db-4-320.jpg)
Cosmos db
- 1. Cosmos DB Overview by Akshat Thakar
- 2. Databases - Background 1. SQL – Normalized Schema, Referential Integrity, Constraints, Indexed data 2. OLTP vs OLAP 3. Teradata, EDW - OLAP 4. NoSQL – Not only SQL use cases i. Document Database – MongoDB Website Visitor profile Case Document of Patient Wheel traceability ii. Column Family Database – Cassandra Gmail with mail Id and mails iii. Graph Database – Gremlin most influential person(s) in a network
- 3. Cloud Concepts High Availability in Cloud Geography Region Region AZ AZ AZ AZ • Failures can occur that affect the availability of resources that are in the same Region and AZ. • AZ may host multiple Data Centers • 54 regions – highest for Cloud provider, public and private regions
- 4. Cosmos DB - Background • IaaS – Compute, Storage and Network • PaaS – Brand of Products – OS, Databases, Middleware as managed service Management and Sizing is planned by Provider • SaaS – Readily available Product – SalesForce, Gmail, PeopleSoft, SAP SuccessFactors • DBaaS [database-as-a-service] 1. SQL Database – Structured Database as service 2. Azure Document DB – NoSQL Database service with support for Document model 3. Cosmos DB – evolution of Document DB with multi model support Supported Models – MongoDB, Gremlin, Cassandra, Table /SQL API ServiceModels
- 5. Globally Distributed • Scale read and write throughput globally. • Maintain business continuity during regional outages. • Globally Distributed – multiple read regions on demand • Low Latency – 10 ms at 99th percentile • Elastic Scalability - thousands to hundreds of millions of requests/sec • High Availability - 99.999% for multi region reads • Tunable consistency – Strong, Bounded Stateless, Session, Consistent Prefix, Eventual. Each model has a tradeoff between consistency and performance.
- 6. High Availability Partitions Logical to Physical Mapping Group of nodes = replication set Container = collection or table London NYC Before MysqLDB1 MysqLDB2 2TB 2TB Total Data = 3 TB
- 7. Pricing Cosmos DB was expensive, now affordable to get started. Before Now Minimum 10000 RU/S with scaling increments of 1,000 RU/S 400 RU/S with scaling increments of 100 RU/S. 1 region - $584 per month Multi Region - $1,168 per month 1 region - $23.36 per month Multi Region - $46.72 per month RU/S – Request Unit per second
- 8. Best Practices • Cloud keep a close eye on your usage. • Scale on Demand – Is complete size estimate needed before deployment? • Test production scale data in Test environment • Technology Stack evolution with multiple model support • Supports Manual Failover of region. Simulate failure and plan. • Leverage automatic secondary indexing • If using MongoDB API, get started using emulator.