The development of storage for data has changed from bulky localized iron servers to the nimble intelligent distributed system that is the cloud. The past was when databases were database was just a single fault point a monolithic unit which was based on a particular part of the hardware.
In the event that the hardware was damaged then the enterprise was dead. We are now in a time of cloud native database.
Cloud native databases are cloud native database is not only its a database that runs in a virtual machine. Its a database system that was built from scratch to make use of the distinct attributes of cloud based computing such as flexibility global distribution and the ability to decouple resources.
This guide offers a thorough review of the 10 most popular real world cloud native databases outlining their architecture and the best way for beginners to get started with them.
What Defines a Cloud Native Database?
Before examining particular instances its important to know the architecture concept. True cloud native database typically adheres to the following fundamental concepts:
- Decoupled storage and compute: The ability to increase the size of your “brain” (processing) independently from the “memory” (storage).
- Elasticity It can expand or contract by itself based upon real time data without any manual effort.
- Resiliency Inbuilt failover systems to ensure that data will not be lost even when all data centers go offline.
- API Driven It is managed through codes and scripts automated instead of manually configuring.
1. Amazon Aurora (The Relational Powerhouse)
Amazon Aurora is perhaps the most widely known model of a cloud native database. Its completely compatible with MySQL as well as PostgreSQL but it has been rewritten specifically for the cloud.
- The Structure: Aurora uses a Log structured and distributed storage system. instead of writing the data onto one disk the system replicates it through six different ways over three Availability Zones.
- Real World Use Utilized by companies such as Airbnb as well as Netflix for handling huge workloads in relational systems that need the highest level of consistency.
- Beginning Steps: You can start by creating an Aurora “Serverless” cluster which is shut down if it is not being used which makes it extremely affordable to learn.
2. Google Cloud Spanner (Global Consistency)
Cloud Spanner is a singular creature. Cloud Spanner is the only managed database to provide an opportunity to attain the “holy grail” of data which is global scale paired with the strictest “external” consistency.
- The architecture: This uses Atomic Clocks as well as GPS receivers within Google data centers to sync the time. This allows it to handle transactions across different continents with no data conflict.
- Real World Use International financial systems in which the balance of a bank account should be the exact same regardless of whether it is you check it at Tokyo as well as New York.
- Starter Step 1: Make sure you are the development of “TrueTime” concepts. Spanner employs a different version of SQL which means that your current knowledge will transfer well.
3. MongoDB Atlas (The Document Leader)
MongoDB Atlas is the cloud based version of the widely used NoSQL database. It is a flexible database that stores data JSON like flexible documents.
- The architecture: It features “Global Clusters” which allow the user to bind data on specific regions of the world in order to comply with local law (GDPR) and still maintain one worldwide database view.
- Real World Application: Systems for managing content catalogs of products mobile app backends and catalogs of products.
- Beginning Steps: Use the “Free Tier” on Atlas to develop a straightforward application for task tracking. Its the simplest method of understanding the non relational information.
4. Amazon DynamoDB (Serverless Speed)
DynamoDB is a key value and document database which provides single digit millisecond speed at any size. Its “serverless” meaning you do not manage servers.
- Its Architecture The HTML0 architecture uses heavy Sharding (partitioning) to distribute information across a multitude of servers. Access to the data is through HTTP APIs not permanant connections.
- Real World Application: Amazons retail website utilizes DynamoDB to manage the huge increase in traffic during Prime Day.
- Beginning Stage: Learn the difference between an “Partition Key” and a “Sort Key.” This is the key to getting the most out of DynamoDB performance.
5. Snowflake (The Data Warehouse)
Snowflake changed the way data is processed in the way it separated compute from storage. It was designed for analysis and not for transactional data.
- The architecture: The HTML0 architecture is based on a “Multi cluster Shared Data” architecture. It is possible to have 10 different teams each querying the same data at once and not slowing one another down.
- Real World Application: Big analytics of data for big enterprises.
- Starter Instructions: Explore Snowflakes “Time Travel” feature that lets you query the data at any time within the last 90 days.
6. Azure Cosmos DB (Multi Model Flexibility)
Microsoft Azures primary database was designed to work at “massive scale.” It is able to support several “APIs” meaning it is able to function like the document database as well as a graph database or Key Value storage store.
- The architecture: The HTML0 architecture offers 5 distinct “Consistency Levels” ranging from “Strong” (slow but accurate) up to “Eventual” (fast but potentially old).
- Real World Use Gaming and retail on a large scale that require low latency internet access for all users.
- Beginning Stage: Experiment with the “Change Feed” feature which allows you to create the code (Azure Functions) when data stored in the database is changed.
7. CockroachDB (The Survivable SQL)
The name is derived from its capacity to withstand almost any situation CockroachDB is an open source database that is open source distributed SQL database.
- The Structure: This architecture employs an algorithm known as the “Raft” consensus algorithm. Data is cut into a range and then every range is duplicated on various nodes. When a node is killed and the rest of the nodes “vote” on a new leader.
- Real World Use Multi cloud deployments when companies want to operate the database over AWS in addition to Google Cloud simultaneously.
- Beginning Step: Install the “CockroachDB Dedicated” free version. Test taking down nodes (servers) to test how the database is kept up and running.
8. PlanetScale (The Vitess Engine)
PlanetScale is a MySQL compatible serverless database platform based on “Vitess” the technology YouTube utilized to expand its huge database.
- Its Architecture The HTML0 architecture introduces the idea of “Database Branching.” Similar to how you branch code within Git You can divide the schema of your database schema modify it to it then merge them.
- Real World Application: The modern teams of DevOps who wish to manage their database modifications using the same care like their code for applications.
- Beginning Steps: Make the “Deploy Request.” Its a safe way to change your database schema without the risk of causing downtime.
9. Google BigQuery (Serverless Analytics)
BigQuery is Googles controlled petabyte sized data warehouse. BigQuery is “columnar” meaning it is able to read data vertically instead of horizontally.
- The architecture: The HTML0 architecture uses “Dremel” technology to transform the same SQL query into a myriad of tasks that can be executed on the vast array of computers within a matter of seconds.
- Real World Application: Analyzing billions of records or data from marketing details in a matter of just a few seconds.
- Beginner Step: Use the Google Cloud Public Datasets. It is possible to query Terabytes of Wikipedia and weather information at no cost to test the speed of data.
10. Neo4j Aura (The Graph Expert)
Neo4j is the most popular graph database as well as Aura is its cloud based service. It is focused on connections between the data points.
- Its Architecture Contrary to the relational database which relies on “Joins” Neo4j uses “Index free adjacency” making it extremely efficient in moving through complicated networks.
- Real World Application: fraud detection social network connections as well as recommendations engines.
- Beginning Stage: Learn the “Cypher” query language. Its much easier as SQL to find relationships between products or people.
Step by Step Guide: How to Choose and Implement
If youre just beginning trying to set up an cloud native database take these actions:
Step 1: Identify Your Data Structure
- If your data is extremely organized (like the ledger) then you should consider Amazon Aurora.
- If your data has a lot of flexibility (like the user profile) choose MongoDB Atlas.
- If the data you are collecting is related to connections (like the social map) then you should use Neo4j Aura.
Step 2: Choose Your Scaling Model
- Provisioned Choose the size of your server (Good for predicting cost).
- serverless Cloud providers determines the size of its cloud based on usage (Good to use for apps that have frequent utilization).
Step 3: Set Up a Budget Alarm
Cloud based databases can be scaled to infinitely and consequently their cost. Set an “Budget Alert” at $5 or $10 prior to exploring.
Step 4: Focus on High Availability
If you are setting up your first instance make sure that “Multi AZ” (Multi Availability Zone) is activated. This is a major benefit of cloud computing. It makes sure that the database is able to survive if one center is affected by a power failure.
The Future is Distributed
The times of coordinating physically database servers are about to come close to coming. Being aware of cloud native database technology is no longer an option requirement for developers. It is now a necessity. If you decide to go with the power of relational databases like Aurora or the broader range of Spanner or the server less ease of DynamoDB youre building upon a base designed to meet the needs of todays 21st Century.
Through separating storage and compute and by embracing distributed systems these 10 databases enable users to develop applications that run faster safe more secure and flexible than the ones that came before them.
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