NCache Architecture

Distributed Cache for .NET
Open Source
Iqbal Khan
Technology Evangelist
www.alachisoft.com, @NCache
Architecture
1@NCache Architecture www.alachisoft.com

The Scalability Problem
Application Tier Scales Linearly
BUT
Data Storage is the Bottleneck
(Relational Databases, Mainframe Data, etc.)
NoSQL Database Not Always the Answer
(often unable to use it)

Linear Scalability of NCache
3
NoSQL Database
Any NoSQL DB
Relational DB
SQL Database
- Low cost servers
- Data replication
- Cluster wide updates
NCache Dynamic Cluster
Windows 2008/2012 (64-bit)
Linear Scalability
Memory & CPU pooled
100% Traffic
20% Traffic
Legacy Data
Mainframe
Web Apps (.NET & Java) Web Services (.NET & Java) Server Apps (.NET & Java)
@NCache Architecture www.alachisoft.com

NCache Scalability Numbers
50,000
72,000
96,000
120,000
144,000
32,000
48,000
64,000
80,000
96,000
-
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
2 3 4 5 6
Txns/Sec
Cache Servers
Read/Sec
Writes/Sec

Common Uses of NCache
1. App Data Caching
– Cache linearly scalable (database is not)
– Data exists in BOTH cache & database (permanent data)
2. ASP.NET & ASP.NET Core Caching
– ASP.NET Session State storage (single-site & multi-site)
– ASP.NET View State cache (pre-MVC)
– ASP.NET Output Cache provider (ASP.NET Core Response Caching)
– Data exists ONLY in cache (transient data)
3. Runtime Data Sharing thru Events
– Event driven data sharing in pub/sub model
– Event notifications & Continuous Query
– Data exists ONLY in cache (transient data)

Self-Healing Dynamic Cluster

High Availability (100% Uptime)
Self-Healing Dynamic Cluster
 Peer to Peer Architecture
 No single point of failure
 No master/slave or majority rule
 Runtime Add/Remove Servers
 Without stopping anything
 Connection Failover Support
 Between clients & servers
 Within cache cluster
 Dynamic Configuration
 Cluster membership propagated Dynamic Cache Cluster
NCache Srv
Add
Server
At
Runtime
Remove
Server
At
Runtime
NCache Srv NCache Srv
Cache Clients (Web/App Servers)
Cluster
Membership
Info
Cache
Topology Info

Caching Toplogies

Caching Topologies
Mirrored Cache (2-node active/passive)
Server 1 Server 2
Mirrored Cache
1 2
3 4
5 6
Active
1 2
3 4
5 6
Passive
(Backup)
Async Mirroring
• 2 Nodes (Active & Passive)
• Clients Connect to Active Node
• Active Node has Entire Cache
– Passive node has a copy
• Async Mirroring
– Passive node becomes active
• Auto Failover Support
– Passive node becomes active
– Client auto-connect to it

Caching Topologies
Replicated Cache
• All Nodes are Active
– Can be more than 2
• Entire Cache on Each Node
– Multiple copies of cache
• Client Connects to One Node
– Auto load balance
– Manual node selection
• Synchronous Updates
– Sequence based algorithm
– Slower than async options
Server 1 Server 2
Replicated Cache
1 2
3 4
5 6
Active
Synchronous Updates
1 2
3 4
5 6
Active

Caching Topologies
Partitioned Cache
 Partitions & Distribution Map
 Automatic division of cache into
partitions
 One partition per cache server
 1000 buckets per cache cluster
 Buckets distributed evenly
 Clients Connect to ALL servers
 For single-hop data access
 Data Balancing
 Moves buckets to other partitions
 When partition is added or removed
 When partition overloaded
Server 1 Server 2
Partitioned Cache
21
Partition 1
43
Partition 2
Distribution
Map
Distribution
Map

Caching Topologies
Partition-Replica Cache
 Replicas of Partitions
 Created automatically
 On a different server
 Are passive (no client talks to
replicas). Only partition talks to it.
 Async Replication (default)
 Async replication is BULK copy
 Could lose some data
 Sync Replication
 Done as part of operation
 Operation fails if replication fails
 Data Balancing on Replicas Too
 When done on Partitions Server 1
21
Partition 1
43
Replica 2
Distribution
Map
Distribution
Map
Server 2
43
Partition 2
21
Replica 1

Server 1
21
Partition 1
43
Replica 2
Distribution
Map
Distribution
Map
Server 2
43
Partition 2
21
Replica 1
Server 1 Server 2
Partitioned Cache
21
Partition 1
43
Partition 2
Distribution
Map
Distribution
Map
Caching Topologies
Partitioned Cache & Partition-Replica Cache

Caching Topologies
Data Balancing on Adding/Removing a Server
Server 1
21
Partition 1
Replica 3
65
Server 3
65
Partition 3
Replica 2
43
Server 2
43
Partition 2
Replica 1
21
Partition-Replica CachePartition-Replica Cache
Server 1
21
Partition 1
43
Replica 2
Server 2
43
Partition 2
21
Replica 1

Client Cache (Near Cache)

Client Cache (Near Cache)
 Local cache (close to your app)
 InProc or OutProc
 Sync with cache cluster
 Auto sync
 Optimistic & pessimistic sync
 No code changes needed
 Automatically intercepts cache calls
 Use in read-intensive cases Dynamic Cache Cluster
Client Cache
. . .
Client CacheClient Cache
SynchronizedSynchronized Synchronized
Cache ServrCache Servr Cache Servr
Client Cache
Any Caching Toplogy

WAN Replication
(Multi Datacenter Support)

WAN Replication of Cache
Active-Passive
Active-Active

API Overview

App Data Caching API
• Connect & Disconnect from the Cache
• Cache cache = NCache.InitializeCache(“myDistributedCache”);
• cache.Dispose();
• Read from the Cache
• Employee employee = (Employee) cache.Get(“Employee:1000”);
• Employee employee = (Employee) cache[“Employee:1000”];
• bool isPresent = cache.Contains(“Employee:1000”);
• Add to the Cache
• cache.Add(“Employee:1000”, employee);
• cache.Insert(“Employee:1000”, employee);
• cache[“Employee:1000”] = employee;
• Remove from the Cache
• Employee employee = (Employee) cache.Remove(“Employee:1000”);

Next Steps
• Download NCache (Fully Working 60-Day Trial)
– http://www.alachisoft.com/download.html
• Download NCache Open Source (FREE)
– http://www.alachisoft.com/download.html
• Schedule a Personalized Online DEMO
– One hour long
– Get answers to your questions from our Solution Architects

NCache Architecture

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