Scaling PHP using database structures Sharing session data between multiple servers: Cold fusion, Network File System, Database, Memcached, Redis, Zend server Cluster Manager, Varnish Scaling PHP using NFS Advantages: No changes in the PHP code Disadvantages: Inefficient, not designed for read/write ratio and poor performance & data corruption Scaling PHP using database Session sharing using db Db: MySQL, Ms SQL Server, Postgre SQL, Oracle, etc.
Advantages Solves scalability problems, wide installation base and DB is readily available Disadvantages Sessions have 1:1 read/write ratio, connection overhead, performance issues and single point of failure Scaling PHP using Memcached Advantages: Can store memory in RAM, high availability, works fast and can be clustered Disadvantages: No persistent data and ability to create alternate memory when RAM is full Scaling PHP using Redis Redis is an open source NoSQL database, networked, in-memory,persistent, journaled, key value data store.
Redis supports not only strings, but also sophisticated data types such as lists, sets, sorted sets, hashes and more.
Advantages: Incredibly fast, persistent, reliable and non-blocking Disadvantages: Custom PHP sessions handler, Not scalable and no high availability Scaling PHP using Zend Server Cluster Manager Zend is for large scale PHP deployments; Can build PHP cluster stack involving even hundreds of servers Advantages: Fast, reliable, high availability, Scalable & No changes in PHP code Disadvantages: Zend server support on each node of cluster Scaling on cloud hosting Scaling out With "cloud-hosting", all of the above steps are redundant and handled internally.
if you want to scale out from 1 to 5 servers, You can automatically carry out those 4 steps in just 30 seconds.
From the management console you only have to move the scale-slider from 1 to 5 and hit the "Confirm" button.
This is called "easy scaling" in our parlance.
Scaling down Deploying a new version is also easy, you just push a new version via git push and your code automatically gets distributed to all the servers in just 30 seconds.
Scaling on Cloud using Amazon DynamoDB Amazon DynamoDBis the fully managed NoSQL database service offered by Amazon Web Services- as a scalable session store.
Advantages: Native session handling, Create table to store sessions, easy, fast, high performance, scalable, data storage and data transfer fee applicable depending upon size and capacity, designed for read/write ratio with session locking capacity Disadvantages: SQL database at high abstraction level Scaling on Cloud using Windows Azure Successfully manage sessions across multiple instances requires a common data store.
Session handling via Windows Azure Table and Blob storage Advantage: distributed, in-memory,high speed, scalable,secure, read only data, and flexible caching Disadvantages: No support for SQL Azure store for session handling; reading, writing, and deleting of session data is only slightly more complicated;