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Email architectures rely heavily on the performance of servers and disks. Over time, the email has become a very demanding application because of the size of emails and more group collaboration over email. The data requirements of email applications are projected to grow from KBs 10 years ago to MBs now, and to GBs in the future. Without any control over data management, email applications are not benefiting from the advances in high performance storage.

Studies indicate that efficient retrieval of recent data matters a lot to users. Similarly, stale data can be served with higher latency. Searching and indexing requirements for email have also grown in the last decade. In a large workgroup collaboration, sharing of documents and emails that go out to a large number of users with large attachments can stress the servers.

Datagres technology eases the data management issues in the email infrastructure. The added benefits have a clear and visible impact on the user's expectation from the email environment. At the same time, the servers can now host more user-load hence lowering the cost of providing email.

The case study in this document demonstrates the value proposition for Zimbra Email servers. However, it can be used with other email servers as well.




Accelerating the performance of Zimbra Email Server

Zimbra email server offers multiple opportunities for system acceleration. Zimbra receives messages, and writes it to the disk. Zimbra then transfers these messages into the message-store and MySQL database. Some deployments also provide the Lucene indexes. Zimbra authenticates on the LDAP server. Authentication is mostly reads but sometimes the last-login-time etc. may also be stored.

Similarly while reading information from Zimbra via WEBMAIL, POP or IMAP protocols, the app server performs authentication on the LDAP and reads the messages from the MySQL server and the message-store on the file system. The same process is followed for downloading attachments.

User behavior in the email services follows the pattern of Last-In-First-Read, most of the time. The most recent data is required to be read first as confirmed by the behavior of the WEBMAIL, POP and SMTP protocols.




The results below show that the overall gain in both SMTP and POP transactions in 'Ops per minute' is 3X with a very low cost Intel SATA SSD and PerfAccel Software from Datagres that intelligently manages the data for acceleration purposes.

This means 3X faster WEBMAIL, POP and SMTP transactions on the same server architecture. Not only does the end-user observe faster email but the server utilization is also reduced by 3 times. Datagres PerfAccel thus provides an overall amplification of 9X times for Zimbra deployment. No integration with Zimbra is required from the Datagres PerfAccel Software perspective.








The total-ops is the sum of all transactions that happen inside Zimbra, given a POP or SMTP workload:




With PCIe SSD cards it is also possible to accelerate SMTP and the load of incoming email to the server, to a much higher acceleration factor.

  Following are the key features of the Datagres PerfAccel Software
  Intelligent caching accelerates data access by reducing the time taken for an IO operation
The customer's email files are intelligently pre-fetched in the cache at 9am before the rush builds up
When a large email attachment is sent to a large number of users, the concurrent reads for that email return much faster
More number of concurrent users are hosted per server and the cost of the server is reduced
Index files are kept in the cache forever
Logging servers use write-back caching
Number of queries on MySQL can be increased to thousands per second
Multi Tenant Control relieves user from locking SSDs only for one application or for one device
Relieves users from the burden of manual management of data on SSDs
Can accelerate currently existing data on ext2, ext3 or NFS file systems
Supports iSCSI devices
To understand the caching behavior, customers can use analytical mode to understand the application workload without any SSD
Caching mechanism is completely manageable by the user
File Level Cache Management is available
Single Point of Management Interface
Graphical Usage Analysis available to trace IO bottlenecks