What is Cosmos DB Azure?
Microsoft Azure Cosmos DB offers a distributed NoSQL database service supporting multiple models. Adaptive in nature, its data types support include document, graph, key-value pair, and column-family data types.
Cosmos DB Supports Multiple Data Models
Cosmos DB can meet the diverse data models across modern applications without needing multiple databases or complex migration procedures. Its flexible data modeling features enable Cosmos DB to meet this need without incurring additional database charges or costly data migration efforts.
Cosmos DB is a Globally Distributed, Scalable
Cosmos DB replicates data automatically across Azure's global data centers to ensure high availability, low latency access, and improved performance for its global user base. Furthermore, its scaling options accommodate fluctuating workloads, making it suitable for large, globally distributed applications.
Cost of Cosmos DB for Azure
Cosmos on Azure costs are determined by database throughput and storage needs, number of request units, data transfer speed, and transfer volume. At the same time, it may cost more than MongoDB in Azure for its global distribution capabilities and data transfer features.
Does Cosmos DB in Azure work the same as MongoDB?
Cosmos DB and MongoDB are two NoSQL database services on Azure that differ significantly in features, data models, and use cases - it all depends on what suits your application or business goals best! Choosing between Cosmos DB or MongoDB depends entirely upon these considerations and business goals for which one will ultimately make its choice easier.
Benefits of using Cosmos DB instead of MongoDB
The following are some of the benefits of using Cosmos DB rather than MongoDB:
- Global distribution Cosmos DB's global replicating capabilities enable low-latency access for users worldwide and help maximize performance.
- Multimodel Support: Employing multiple data models within one database reduces complexity in data integration and simplifies development efforts.
- Scalability Cosmos DB features automatic scalability to easily handle fluctuations in workload, making it suitable for applications with unpredicted demand.
Benefits of Azure Cosmos DB
Speed is guaranteed at all scales:
- Fast Read and Write Latencies Available Worldwide
- Data distribution can be simple and multi-regional.
- Scale your storage and performance across any Azure region autonomously and flexibly.
Simplified application development:
- Azure Services used for cloud-native Microsoft Azure development services are deeply intertwined.
- There are multiple database APIs, including API for SQL, MongoDB API, Cassandra API, Gremlin API, and Table API.
- API is available.
- Build apps using SQL API in any programming language you choose; drivers for other database APIs may also be provided.
- Change feed provides an efficient method for tracking and managing database container changes.
- Azure Cosmos DB's schema-less service indexes your data automatically and is fully managed for maximum flexibility.
Mission-critical ready:
- Azure Cosmos DB provides comprehensive Service Level Agreements (SLAs), such as industry-leading availability.
- Automatic data replication helps effectively distribute information across Azure regions.
- Azure provides role-based access controls that safeguard data security.
Cost-effective and fully managed:
- Fully managed database services will ultimately save developers both money and time.
- Cost-efficient options exist for workloads of all shapes and sizes.
- Serverless models offer an adaptable service that supports workload spikes without disruptions or additional workload.
- Azure Cosmos DB's autoscale provisioned-throughput feature can effectively manage unpredictable workloads by increasing capacity to meet spikes while upholding SLAs.
Want More Information About Our Services? Talk to Our Consultants!
What is Cosmos DB used for?
Cosmos DB can help global applications that demand high availability, low latency access, and efficient data storage develop efficiently and with low latency. Azure Cosmos was successfully employed to construct "GlobaMart," an international ecommerce platform working across many regions around the globe and using Cosmos DB to store customer and order information and replicate automatically across Azure regions for low latency availability and highly available access.
Containers in Cosmos DB were utilized for partitioning data by attributes like customer location or product categories in Cosmos DB containers so data replicated automatically across regions. At the same time, it was highly available across regions for high availability with low latency access across many Azure regions automatically replicated across Azure regions; containers were utilized within Cosmos DB containers when partitioning data by attributes such as customer location or product categories, ensuring data was highly available with low latency or accessibility from multiple Azure regions for seamless global ecommerce operations worldwide ecommerce operations ensuring all data replication was achieved.
Cosmos DB's global distribution feature allows you to place replicas across different Azure regions, giving customers access to their data at the nearest data center and improving performance and latency. Cosmos DB's Scalability features allow dynamic storage capacity adjustment as GlobaMart grows, thus accommodating peak periods like Black Friday.
Azure Cosmos DB provides a tool to develop Azure web service on an international scale and can be found across many industries as a solution for various use cases. Let's examine some of its most prevalent uses today.
Microsoft Azure Cosmos DB Features and Benefits
Azure Cosmos DB is a relational database offering several key features and benefits for modern global applications that need high performance, scalability, and availability. Here are a few notable ones:
Multimaster Support
Azure Cosmos DB's multi-master feature is one of its core advantages. Data retrieval time may be negatively affected due to network latency when stored centrally; with Cosmos DB multi-master support, data can be written simultaneously into multiple global databases, allowing retrieval times to remain fast.
Data Replication
Azure Cosmos DB's multi-master feature ensures data replication across databases and regions, giving users access to their local region without incurring network latency issues - offering users a personalized user experience regardless of where they reside.
Global Distribution
Azure Cosmos DB allows you to manage data across multiple Azure regions with low latency and high availability for maximum application performance regardless of user location. Your application can scale regardless of its geographical origins with ease!
Fast, Flexible App Development
Azure Cosmos DB provides free dev/testing options that allow you to experiment with and prototype your ideas without incurring additional costs. Azure Cosmos DB offers azure website development service to make integrating your favorite programming language easier. It is compatible with open-source databases such as PostgreSQL MongoDB and Apache Cassandra. This allows you to leverage your existing skills and tools.
Consistency Levels
Azure Cosmos DB provides various levels of consistency to enable developers to find an optimum balance between performance, consistency, and availability for their application needs. Azure Cosmos DB currently supports three consistency levels:
- Strong consistency: This level guarantees that each read operation receives the latest data version. While this ensures performance and availability are maintained, synchronous replica and potential latency delays could negatively impact these metrics.
- Bounded Staleness: This level ensures consistency within a specified period, with developers able to adjust its staleness period according to the needs of their application and tradeoff between performance, availability, and consistency as required.
- Session consistency: This level ensures consistency within a user session by guaranteeing data is uniform across writes and reads performed within that same user session. It strikes a balance between performance and consistency for optimal user experiences.
- Consistent prefix : With this level, read operations will never see out-of-order writes; however, read operations may still access older data.
- Eventual consistency: While this level offers the most outstanding performance and availability, it does not ensure data consistency across regions. However, these inconsistencies will eventually settle out over time.
Unparalleled Performance on Any Scale
Azure Cosmos DB provides instant and limitless elasticity to your applications, enabling them to scale without hassles or latency issues. Support for multi-region write capability provides fast reads to reach customers efficiently with minimum latency issues.
Fully managed
Azure Cosmos DB features a serverless architecture, enabling you to only pay for the resources you consume. As it automatically scales resources based on application demand, cost-effectiveness becomes even more incredible; thanks to elastic resource scaling, you won't need to manage or provision database infrastructure, thus significantly reducing operational data overhead costs.
Mission Critical Applications Ready
Azure Cosmos DB provides mission-critical applications with the reliability and resilience needed for smooth running, including SLA guarantees of 99.999 percent availability to ensure applications stay operational even during any disruptions; continuous backups provide an extra layer of data security, while enterprise features like encryption in transit and at rest as well as role-based security controls and compliance certifications help meet regulatory compliance needs are available as enterprise features within Cosmos DB.
Also Read: A Comprehensive Overview of Azure Cloud Security Systems
How Does Cosmos DB Work?
Imagine creating an international ecommerce app using Azure Cosmos DB that requires storing and retrieving information about products, customers, and transactions. Azure Cosmos DB lets you set up containers for various data types to optimize storage and retrieval - customers from around the globe can quickly access your application to retrieve product data through global distribution, while partitioning allows your database to easily accommodate more customers or products. At the same time, automatic indexing enables rapid search capability using various attributes, ensuring customers always see up-to-date product info when shopping with its consistency model.
Why Do We Need a NoSQL Database
Developers across many fields have relied heavily on relational databases in recent decades to develop applications, with relational databases remaining widely employed today. As database and application sizes increased, scaling relational databases proved challenging - leading to greater demand for highly scalable alternatives if applications had to remain available and responsive all of the time; applications must meet high-performance demands, which necessitate distributed scaling models that ensure applications stayed online and responsiveness is at peak level performance at any point in time.
Relational databases rely on relationships for their functionality; expanding these over multiple systems is costly due to maintaining these relationships across each node in a cluster. Because this task was initially intended for running on only a single server to protect their integrity, these relational databases could scale vertically but not horizontally due to increasing server resources (vertical scaling would still work, however); NoSQL databases were explicitly designed to overcome such limitations by being flexible enough to be scaled vertically and horizontally without regard for maintaining relationships.
Introduction NoSQL Databases
NoSQL databases, also called non-relational databases, store information as documents instead of in tables like relational database management systems (RDBMS). Because there are no tables involved with NoSQL databases, there are no relationships between entities as there is no table structure containing records; KVDBs (Key-Value Databases), Columnar Databases (Columnar DBs), Document Databases (Doc DBs), Graph Databases, etc are examples of NoSQL databases. At the same time, JSON is its primary storage format when discussing NoSQL structures. We shall examine how NoSQL Databases are structured today.
Figure 1. depicts two tables, " Orders " and "Order details, "along with a JSON file based on their structure on the right. This file serves as one document within a Document Database; furthermore, orderDetails data has been integrated directly into orders in a nesting format to make reading it faster than reading multiple tables simultaneously. NoSQL stores data as documents, which allows each order to be distributed across different nodes without needing complex relationships between entities being maintained between documents storing detailed orders nested within documents. It does away with complex relationships between entities that need maintaining.
Azure Cosmos DB: The Rescue
Let's examine Azure CosmosDB as a NoSQL provider, according to Wikipedia definition: it "is Microsoft's global-distributed, multimodel database service designed for managing data at planet-scale launched in May 2017 that supports schema agnosticism, horizontal scaling and is typically considered NoSQL". Microsoft introduced CosmosDB in 2017 as an open-source database system capable of accommodating various models; in part two of this post, we will look more closely at them all.
Azure Cosmos DB provides managed services, so customers don't need to be concerned with infrastructure management. Available only to active Azure subscribers, its rich feature set includes global distribution and multi-master replicator modes and storage in multiple locations for data residing therein. Cosmos DB can even facilitate analytical workloads and Artificial Intelligence using stored data.
Azure Cosmos DB Structure
Now that we know more let's understand the structure of Cosmos DB components.
Database Accounts are the highest-level item, as seen in Figure. Within an Azure Cosmos DB Database Account are databases composed of containers; depending on which API was chosen to create NoSQL databases, containers could include different types, such as collections, tables, or graphs. Each container offers unique functionality compared to others (collections contain stored procedures, user-defined functions trigger merge procedures, among others), offering unique sets of features regardless of container API used and type (collection types vary with database API used), which are displayed in Table 4. The table shows how API usage relates to collections/item types/collections/item types related information within Table 5.
Azure Cosmos DB: Key Features
This section will highlight some of Cosmos DB's key features.
- Global distribution: Cosmos DB, an enterprise-distributed database designed with low latency in mind, aims to be used across global organizations as a worldwide distributed database system.
- Linear Scalability: Cosmos DB stands out among database systems as one of the fastest databases capable of supporting multiple read requests every second, giving access to thousands of read requests every second.
- Multi-Model: Cosmos DB integrates multiple database APIs into one comprehensive system, giving users access to Documents, fundamental values, and Columnar, or Graph Databases.
- High Availability : Cosmos DB availability SLAs are much too generous; their multi-region and single-region read-and-write availability SLAs reach 99.9999%, respectively - meaning there will be very minimal downtime, meaning applications can continue running most of the time without interruptions or downtime issues.
Also Read: How Microsoft Azure Is A Perfect Cloud Solution For Smbs?
What is the difference between Azure Cosmos DB Relational Databases and NoSQL databases?
Azure Cosmos DB NoSQL vs Relational Databases is highlighted in the following points:
High throughput
Maintaining a relational system that handles large transaction volumes can be formidable.
Most relational engines utilize locks and latches to enforce strict ACID definitions, thus guaranteeing consistent state data within a database. Unfortunately, such practices also increase complexity by prohibiting data access when ACID rules cannot be strictly adhered to.
- The tradeoffs between concurrency, availability, and latency can be significant.
- Due to architectural restrictions, manual data sharding may become necessary if your transactional columns contain many transactions. Unfortunately, manual sharding can be a consuming, costly, and painful process that must be endured to stay competitive in today's business landscape.
What can Azure Cosmos DB do to simplify this challenge?
Azure Cosmos DB solves these problems by:
- The Azure region includes all major countries.
- If the transactional volume in your business has grown too large to handle, a distributed NoSQL database such as Azure Cosmos DB could provide high availability, easy maintenance, and reduced total cost - ideal if your transactional volume becomes unmanageable.
Hierarchical Data
Maintaining accurate records regarding parent-child relationships is vitally important. Numerous use cases demonstrate how databases may contain multiple parent-child relations that have the potential to become complex over time. Hierarchical databases were devised in the 80s to manage these parent-child relations but eventually failed due to storage inefficiency.
What Can Azure Cosmos Db Do To Simplify This Challenge?
NoSQL Document Databases such as Azure Cosmos DB can handle transactions within databases containing many parent-child relationships and deep levels in the hierarchy.
Check out a Comparison of Relational and Hierarchical Databases by clicking below!
Complex Networks And Relationships
Relational databases offer an effective means of organizing complex networks and relationships, but they also present unique challenges.
- Relationships cannot be stored within relational databases and must instead be calculated at runtime; to keep pace with an ever-increasing network of relationships, computing becomes exponentially more costly as more relationships come online.
These systems, like hierarchical databases, failed to gain in popularity due to:
- Storage inefficiencies
- There were no use cases available at the time.
The graph database engine represents an innovative resurgence of network databases; relationships can be traversed within set periods.
Use Cases of Azure Cosmos DB
Below are the most common use cases of Azure Cosmos DB.
IoT and Telematics
IoT applications involve sensors sending bursts of streaming data directly into a cloud service for processing and real-time analysis before being stored in cold storage for future batch analysis purposes. Microsoft Azure offers many rich services explicitly designed to aid IoT apps, including Event Hubs, Cosmos DB, Stream Analytics, Notification Hub, HDInsight, and Power BI, to name just some examples of IoT application services available through Azure.
Azure Event Hubs provide high-throughput data ingestion at low latency. Azure Stream Analytics now facilitates real-time analysis using streaming data loaded onto Azure Cosmos DB; real-time analyses may use all or only changes. Refine data with HDInsight using Pig, Hive, or Map/Reduce tasks before loading back onto Cosmos DB for storage and analytics.
Social Application
Azure Cosmos DB stores and queries user-generated content like chat sessions, blog posts, and ratings created for mobile and social media applications.
It makes it simple and quick for Azure analysis services developer to store chats, posts, and comments without complex mappings or transformations being necessary; data properties can easily be added or modified when developers make iterations on application code, which speeds up development timescales significantly. This facilitates rapid application development.
Since social networking services require applications to adapt quickly to changing schemas, databases must be schema-agnostic; records should self-describe. NoSQL databases like Azure Cosmos DB automatically index data without regard to schema requirements - making this approach to data management ideal in this instance.
Social applications often run globally with unpredictable usage patterns that require rapid scaling to keep up. Azure Cosmos DB's Autoscale Provisional Throughput feature allows you to adjust its datastore according to increased usage; you can even create multiple Cosmos DB accounts across different Azure regions!
Azure Cosmos DB resource model
Azure Cosmos DB supports four resource types.
- Azure Cosmos DB Account
- Databases
- Containers
- You can also find out more about the products by clicking here.
These resources may differ in meaning depending on which API is being used to access Cosmos DB Account, but are organized hierarchically:
Azure Cosmos DB Account
Conventional database systems enable multiple databases to reside on one physical server for easy access. If problems arise with these databases, we can add more physical servers. With the PaaS cloud application development services there is no such concept of physical servers - rather, an abundance of virtualized instances offering full-service database environments in real-time.
Storage and computers have become virtualized over the years; we need an alternative access point for databases besides simply connecting directly to servers. Azure Cosmos DB Account enables easy access to databases through their unique DNS address, with geo-replicating data for high availability simultaneously improving or decreasing the throughput of databases.
Databases
Through an Azure Cosmos DB Account, you can create multiple databases using any Cosmos DB API.
Your database could have different purposes - sales, marketing, payroll - so using an appropriate security model, groups of users will not have access to each other's data. Furthermore, with isolated stored functions and methods implementing different business logic, we can also scale each database independently to support different throughput levels.
As part of creating databases with Cosmos DB, there are certain precautions you should abide by.
- Table API is the only API container that does not use databases; all tables stored with Table API are kept within an existing one called 'TablesDB.' You cannot alter or replace its contents.
- Cassandra does not refer to their database as "Database." Rather, it uses "Keyspace."
Containers
Containers may initially seem similar to regular database tables; however, their purpose can differ for specific APIs and come in various shapes. When creating them, containers require creating an optional shared key; horizontal partitioning enhances performance, and you can configure Time-To-Live on containers so expired records will be deleted after an appropriate amount of time.
Azure Cosmos DB containers may take various shapes depending on their respective API.
- SQL AP: Cosmos DB provides a Document Container when using SQL API to store documents.
- Cassandra: Cassandra uses Tables as data containers.
- MongoDB API : MongoDB employs a collection for storing BSON documents. Azure Portal's user interface runs MongoDB queries against Azure Cosmos DB Shells for easy query management.
- Gremlin's All Cosmos DB: containers use tables as storage, while Gremlin API uses graphs instead to store its vertices.
- Table API: Table API is a table-based API designed to store key-value information. Originally released under Azure Table Storage, in 2017 this service became part of Cosmos DB products.
Item
Different items must be stored in suitable containers to protect their integrity. ARS models are used to store items which do not match exactly, yet are similar enough for us to query both databases simultaneously - an advantageous feature indeed!
Want More Information About Our Services? Talk to Our Consultants!
Conclusion
This article introduced different kinds of non-relational databases and provided instructions on using Azure CosmosDB for these. Non-relational or NoSQL databases come in four main varieties, Key Value; Document Stores; Columnar Database; and Graph Database. NoSQL databases offer several advantages over their relational counterparts and are becoming increasingly used with modern cloud apps due to being highly scalable both vertically and horizontally - another factor which accounts for their widespread appeal.
