Data in databases are organized in rows and columns into tables for easier navigation and retrieval when required, making life simpler for database handlers who manage many websites online with multiple websites using similar systems of accessing and using databases as management platforms.
Database handlers allow access for users with only a set of software programs installed to access this type of database directly.
MySQL, SQL Server, MongoDB, Oracle Database, PostgreSQL Informix Sybase are among the many examples of databases managed with DBMSs; Structured Query Language or simply "SQL", is commonly used for data manipulation within these systems.
What Is Database Architecture?
Database Architecture of Database Management System design refers to creating, implementing and maintaining database management systems (DBMSs).
With a ranking score of 1244.08, Oracle was the most widely used database management system (DBMS) globally as of June 2024, according to LinkedIn.
A DBMS allows dividing a system up into different components that can be modified independently from each other allowing easy modifications/upgrades/replacements of individual parts within it as necessary - understanding its components is crucial too!
Databases store vital information securely, making data management efficient and effortless. Selecting an effective DBMS architecture will facilitate easy data administration.
Types of DBMS Architecture
Three main types of DBMS Architecture exist:
- One Tier Architecture (Single Tier Architecture)
- Two Tier Architecture
- Three-tier Architecture
- n-tier architecture
We will now learn about the different architectures of DBMS using diagrams.
1- Tier Architecture
One Tier Architecture (in which all three elements (Client, Server and Database reside on one machine), is the basic DBMS architecture.
When installing and using databases for practice SQL queries on personal systems or as learning platforms for practicing queries directly against them a one layer architecture typically used; rarely however are such architectures put into production use.
2- Tier Architecture
Two-tier database architecture (PC, Mobile Device or Tablet) involves having two layers in its architecture that communicate to store information securely; typically this involves having data located on servers rather than being exposed directly to users; it provides more secure communication while still permitting direct and quick exchanges of information between layers.
As evidenced in our two Tier client-server database management system architecture shown here, a server is connected to clients 1, 2, and 3.
Two Tier Architecture Example:This MS Access-built contact management system effectively organizes contacts.
3- Tier Architecture
Three Tier Architecture is one of the more prevalent client-server databases and management system (DBMS) architectures, featuring modularity that facilitates separate development and maintenance modules for logic, functional processes, data access/storage/user interface and data storage/use.
Three Tier Architecture comprises both presentation layer and application layers.
The 2-tier client/server architecture is expanded upon by the 3-tier database architecture.
The layers of a 3-tier architecture are:
- Presentation layer (your PC, Tablet, Mobile, etc.)
- Application layer (server)
- Database Server
N-Tier Architecture
The N-tier architecture involves dividing the application into 3 different tiers. These would be the
- Logical Tier
- The presentation tier is the highest tier.
- The data tier.
Contrast MVC with its physical separation of elements; as opposed to being separated logically or conceptually in many instances.
Furthermore, an n-tier layer structure differs significantly as all communication must go through one centralized logic layer whereas in MVC all interactions take place triangularly between view, model and control layers with access granted between these three.
MVC framework and an n tier architecture do not exclude each other; they both can co-exist together without hindrance from either architecture choice.
High Availability Database Definition
High availability refers to databases which feature higher than usual uptime agreements, achieved through eliminating single points of failure and switching seamlessly to redundant servers; monitoring faults continuously so as to initiate failover promptly at just the right moment; eliminating single point failure; switching off servers when possible and monitoring faults to initiate failover; high availability databases are capable of reaching this uptime threshold without interruption even with network latency or hardware malfunction.
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What Is High Availability?
A High Availability system (HA) is designed to run continuously without interruption. It doesn't necessarily mean that the system will never make errors.
However, it is designed with enough redundancy to deal with errors without causing wider failures.
What Is A High Availability Database System?
A High Availability Database (HA) is a database designed to run continuously without interruptions. Database errors and failures are handled by switching to redundant nodes automatically when problems arise.
How Does Developers.Dev Support High Availability SLAs?
Service Level Agreements (SLAs) are one of the cornerstones of client commitment, and Developers.Dev can assist in fulfilling them.
With its configurable replication factor (RF), which determines where each piece of information will be stored across nodes - typically three will suffice in many high-availability systems - Developers.Dev uses network topology replication across data centers allowing each datacenter to have different replication factors (RF=3 for instance in one main datacenter while satellite locations could have just two).
Developers.Dev staggers data distribution across partitions to prevent an overload on a cluster when either an entire node, CPU or nodes fail.
Their high availability architecture also accounts for racks and datacenters - meaning nodes may be distributed across different racks within one datacenter or even across several data centers, ensuring your NoSQL databases will still remain available even if an entire rack or datacenter disappears - to make your NoSQL databases still remain online even in such circumstances.
Developers.Dev NoSQL databases may become temporarily inaccessible due to server restarts or temporary node loss, in such instances Developers.Dev can maintain hinted handoffs (write, update and delete operations for temporarily unavailable nodes) until its return.
On rejoining, all hinting handoffs will be delivered back into its cluster.
How Can A High Availability Database Eliminate A Single Point Of Failure?
Single Point of Failures are inherent to any form of high availability database; any component which could potentially cause downtime if it were to fail must be eliminated to achieve complete uptime and availability for users.
A High Availability Database must thus eliminate these points of failures through peer to peer relationships among database nodes that communicate between themselves without going through central hubs; developers.Dev employs multiple IP addresses rather than routing all traffic through one central IP address as this eliminates these potential points of failures altogether.
What Are The Common Use Cases For High Availability Databases?
High availability database solutions were once only intended for mission-critical applications such as emergency services or enterprise IT systems, yet users now expect any web platform they use will always be accessible at all times - while some businesses post notices about maintenance windows; instead movie streaming sites, social media websites, and any application connected to the Internet must always remain accessible at all times.
How Is High Availability Generally Achieved?
An effective high availability architecture eliminates all single points of failure by including at least one cluster with high availability nodes that distribute queries and transactions evenly among them to keep the system responsive at all times.
Read More: What is the Most Important Benefit of an Enterprise Application?
How To Ensure High Availability?
An essential aspect of creating a highly available database architecture is having enough nodes for optimal load distribution and consistency requirements, to enable a more responsive system.
Understanding your application is the first step toward designing such an infrastructure; more nodes may not always be beneficial.
What Is The Difference Between High Availability And Fault Tolerance? Fault Tolerance?
When discussing database high availability, our minds often wander towards traditional relational databases with failover strategies like shipping logs.
Consider cloud replication; Azure database high-availability or AWS high-availability databases come to mind as they offer near real-time replication of read-only copies of databases in near real-time, providing fault tolerance.
NoSQL database high availability systems extend beyond simple copies. NoSQLs high availability depends upon spreading transactions and storage loads over one or more clusters of high availability databases in different global regions or Availability Zones.
Traditional databases are built for fault tolerance by providing high consistency data even during component failure and restricting any addition of new data that might lead to anomalies or inconsistencies, prioritizing correctness over availability.
Modern NoSQL databases with high availability prioritize read/write access even if this means inconsistent or dirty writes; their primary priority being availability over accuracy of information stored within.
What Are The Drawbacks To High Availability Database Systems (HADS)?
The CAP Theorem states that distributed databases possess three key properties: consistency, availability and partition tolerance.
A high availability database typically prioritizes two of these characteristics over all three, thus restricting themselves to just two of these properties; developers.Dev is specifically built around partition tolerance ("P") and high availability ("A") therefore its considered an "AP" system - data will eventually reach consistency among nodes but only gradually.
Space requirements of multiple nodes and redundant data copies is another complication for developers.Dev, so we employ several strategies for compaction to minimize redundant copies.
Strategies to Increase Availability
In order to design a highly-available database, we eliminate single points of failure in internal database components and run a duplicate database copy.
Internal Database Components
Redundant Storage
Use multiple redundant hard discs designed to withstand single drive failure in RAID 5 and 10 systems; such as block storage which reduces the chance of drive failure by providing redundant disc support.
Both RAID setups support redundant hard discs.
Using Data Partitioning
Data partitioning allows for storage and grouping at various locations, typically for advanced database designs.
Partitioning can improve performance, security and scalability by spreading writes/reads across multiple disks - also increasing availability because this eliminates single point failures.
NoSQL databases typically handle their partitions differently from relational ones.
Google Cloud allows relational databases to use native partitioning for NoSQL databases while partition keys provide unique codes that organize each document for high availability purposes.
Each partition should preferably reside on its own drive for best performance.
External Database Components
We will first discuss how to synchronize data between the two copies of the database.
Data Synchronization
It is essential that both databases contain identical data. Since synchronized write operations from one database will inevitably reach both, data must exist in both to be successful.
Primary and standby in Different Zones
Doing this may reduce single points of failure within your infrastructure layer - service providers or data centers, for instance - which in public cloud environments consist of one or multiple datacenter zones.
For optimal solutions that do not depend on availability being affected by failure in one zone, databases should be distributed among various zones with high bandwidth connections (100 Gb or greater) connecting them together.
Should one failover zone experience issues, traffic would automatically routed towards an alternative database located somewhere else within another zone ensuring continued service availability - Cloud SQL supports auto-failover across various zones!
Standby and Primary in Different Regions
Public clouds offer up to 99.99% availability through multiple zones; however, certain applications require even higher uptime rates; multi-region architecture can offer up to 99.99% in these instances; some Google cloud databases like Spanner or Big Table include multi-region auto-failover capabilities built-in.
How Can We Achieve It?
Now that we know your plan of attack is set in stone, let's discuss its implementation. Adding more components will not ensure more stability or high availability; adding them could actually increase its probability.
Modern designs often distribute workload across several instances like clusters or networks to optimize resource use while optimizing output, response times and avoid overloading any system - this process is known as load balancing while failover systems allow resources such as servers or components to switch automatically in case one goes offline due to failures or breakdowns.
1. Use Of Multiple Application Servers:
Imagine having only one server providing services. A sudden increase in traffic causes it to crash; once this occurs, any more requests cannot be served until it is restarted.
Of course it goes without saying that when it comes to application deployment across multiple servers, load should be evenly spread between all of them so no single server becomes overburdened and output remains optimal.
Different parts of your app could even be located on separate servers: for instance you could designate one server solely to manage mails while another manages static files like images (similar to Content Delivery Networks).
2. Scaling Databases
Databases have quickly become the go-to choice for user data storage, and are essential components of services and application servers alike.
Unfortunately, databases run on individual servers such as Amazon RDS which make them vulnerable to crashes; when this occurs data loss could prove costly indeed.
Redundancy enhances high-availability systems by improving failure detection and eliminating potential causes. Slave servers can take over in case the primary server crashes; another method for scaling databases involves creating horizontal partitions where each row resides on separate servers (sharding).
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3. Diversify Geographical Locations
Scaling up your database and applications is an enormous leap forward, but what will happen if something like Hurricane Irma strikes the datacenter where these servers reside? This could cause massive downtimes.
Your servers must therefore be spread throughout various geographic locations. Modern web services allow you to select where exactly they sit - make the wisest selection so your servers are spread throughout the planet, not in just one region!
We hope that in this article we have covered the fundamentals of high availability architecture. No single system will address every challenge; instead it is important to carefully assess your circumstances and select suitable options for implementation.
My hope is that this article has given you more of an understanding of high availability architecture as a concept and how best to achieve it.
What Are The Best Practices For High Availability?
High-Availability (HA)architectures can help prevent system failures and minimize both planned and unexpected downtime, especially for mission-critical applications.
According to experts in availability, all components should be well designed and carefully tested prior to deployment in order to make any system highly available.
Although developing and implementing one can be complex given all available hardware/software/deployment solutions, successful efforts usually start by clearly outlining business requirements with regards to security levels, scalability levels, performance etcetera.
High availability is the cornerstone of computing environments that meet production objectives during their normal operational hours, helping enterprises maintain critical applications online while designing architecture properly and adhering to best practices for high availability.
Data Backups and Recovery
An effective backup and recovery plan is at the heart of any good data protection strategy, providing protection from system failure.
Never store valuable information without backup, replications or the capability of recreating it if something goes amiss in data centers or servers; data errors can result in customer authentication problems, financial account damages and loss, credibility loss in business communities.
For optimal data integrity it is advised to create full database backups regularly then test servers incrementally for corruption; additionally full system backups should also be created as precautionary measures in case catastrophic events happen within server or system servers or server environments.
Clustering
All application services will eventually experience issues, even those created with expert software engineers. High availability refers to providing service even during interruptions; clustering enables instantaneous failover in case of errors.
Cluster-aware application services can utilize resources from multiple servers simultaneously and fall back onto secondary ones if their primary server goes offline.Multiple nodes share information through shared memory grids in high-availability clusters.
Virtualized clusters enable each node in a virtualized cluster to continue working normally even if one node disconnects from or shuts down, providing seamless operations while upgrading and rejoining individual nodes as required.
Virtualization also reduces costs when buying additional hardware by making use of existing resources available within existing hardware infrastructures.
Network Load Balancing
Load balancing can be an excellent way to increase the availability of web-based applications. When one server goes down, its traffic is automatically redistributed among others and load balancing provides not only high availability but also allows incremental scaling - with pull or push models both being effective methods allowing greater fault tolerance in service applications.
Failover Solutions
Generally speaking, high availability architecture consists of loosely coupled servers with failover capability.
Failover refers to a backup mode of operation in which functions from one system can be taken over by another should their primary one fail, due to failure or planned downtime, with either cold failover (starting only after primary server has shut down completely) or hot failover (load spreading evenly among all servers at same time), automatic task transfer between systems occurring seamlessly for users while using DNS as control tools in controlled environments for manageability of failover operations.
Geographic Redundancy
Geo-redundancy offers the only practical means of mitigating service failure in the event of a catastrophic event, like a natural disaster that disrupts system outages.
Just as with geo-replication, multiple servers should be distributed geographically across distinct locations - not limited to just one.
In each site it's crucial that if an application stack goes offline one will still run; an ideal scenario would involve total separation among these locations.
Plan for Failure
Though adopting best practices for high availability is planning for failure, additional measures can be taken by an organization in order to be better prepared in case a system failure leads to downtime.
Organizations can utilize data on failures or resource consumption by employees to analyze trends and spot problems within their operations, providing continuous monitoring of operational workload.
Recovery help desks could help businesses quickly collect information on issues that need addressing and begin solving immediately, providing documentation of history as well as unplanned interruptions that require recovery plans to be tested regularly and implemented quickly.
Staff who undergo availability engineering training will become better at designing, deploying and maintaining high availability architectures.
Implementation of security policies may also help decrease system failure due to security breaches.
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Conclusion
Businesses and architects should take the applications uptime needs and cost into account when developing a high-availability database architecture.
In order to create a successful solution with the appropriate availability, it is important to comprehend the business requirements.
This will result in satisfied and devoted clients.
developers.dev is focused on providing you with the best solution possible, without over-architecting and expensive solutions.
Our database consultant services are available to work on or off site using either onshore or overseas delivery.
