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FAQs

What is the ScaleArc software?

ScaleArc (formerly iDB) is a new kind of database traffic management software that, for the first time, offers a transparent way to scale for higher application availability and performance – without any modifications to existing applications and databases. Currently in its third generation and used in mission-critical relational database environments, the ScaleArc software ensures complete compatibility and transparency. Its sophisticated architectural and implementation approach are reflected in multiple patents (pending) for transparent database scalability and caching with additional filings on the way as the ScaleArc R&D team continues to innovate.

Which databases does ScaleArc support?

We support MySQL v5.x and compatible databases (which means it also works with MariaDB, Drizzle, Percona Server, ScaleDB etc.); MS SQL Server 2005, 2008, 2008R2 and 2012; and Oracle, in controlled availability.

How can I get the ScaleArc software?

ScaleArc software is available as traditional software; as a virtual appliance for VMWare, XenServer, KVM or HyperV hypervisors; and in the cloud.

What is Read-Write Split? How is it important for scalability?

Most users scale MySQL by adding additional slave databases, or both additional masters and slaves. Doing so in a conventional setup requires users to modify their application to redirect and load balance read queries (the SQL “select” command) between both masters and slaves, and to ensure that any write queries (SQL commands “insert”, “update”, or schema changes, etc.) are sent to masters. This is complicated and not necessarily best done at the application level. ScaleArc software allows you to configure specific servers in a cluster to act as either a master or a slave, and automatically routes read queries to both masters and slaves while making sure that any write queries go only to masters. This is a transparent process, and does not require any application modification.

Which replication topologies are supported by ScaleArc?

ScaleArc supports all possible replication topologies used by MySQL, SQL Server and Oracle, be it Master-Slave, Multi-Master, Multi-Master-Multi-Slave, Percona xtraDB Galera, NDB cluster, Peer-2-Peer, log-shipping, SQL mirroring, Always-on, Oracle RAC, or even shared disk databases. ScaleArc is replication technology agnostic. ScaleArc also has a built-in replication monitor that makes sure that all servers are in sync at a given time. If a server falls out of sync, ScaleArc will reduce the load on that server to give it the opportunity to recover. If the server fails to recover, and falls further out of sync, ScaleArc can be configured to stop sending queries to that server.

How does ScaleArc’s Transparent SQL Caching work?

Once your DB traffic is flowing through ScaleArc, it is simple to activate SQL caching. You can setup Regular-Expression rules, which can be created manually by the user or automatically by ScaleArc’s built-in analytics GUI, for those queries you want to cache, and designate the length of time you would like the caching to remain in effect (the so-called “Time to Live” or TTL). For example, a simple “.*” expression with a TTL of 60 seconds will cache all select queries for a period of 60 seconds, whereas a more specific pattern of “select * from table2 where userid=.*” with a TTL of 10 minutes will cache only queries that match this specific pattern for 10 minutes. Once you select the pattern, usually by clicking on an existing query to use its pattern as a regular expression, and set the TTL, activating the cache is just a click away.

How fast is ScaleArc’s Cache?

For simple point queries like “select * from table1 where id=x” where the resultant data is pretty small, and the resource utilization on the DB server fairly minimal, the performance difference could be as much as 2x to 3x. When it comes to more complicated queries with more resource utilization (where sorting or text-searches are involved, or more than one result is returned for a query) and on larger tables, the cache could be as much as 50-60x faster. Basically, the more complicated the query, the more the benefit from caching. Also, since ScaleArc’s cache is at the TCP Layer, it can pump data out at a much greater pace than a database server.

How long does it take to deploy ScaleArc for Amazon EC2/RDS?

Just sign up for the product, launch our AMI, use the wizard to setup your cluster, and configure your application to connect to ScaleArc instead of your EC2/RDS DB servers. Once you have your application executing, it takes only a few minutes to start getting SQL analytics data. Now just cache the queries you want instantly.

How long does it take to deploy ScaleArc in my environment?

The installation itself can be very quick within 15 minutes. Within the first hour of the installation customers can view the SQL analytics data and start working towards the cache rules. While every case is different, most customers go live with their ScaleArc implementation within 2 weeks after internal testing.

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