Last weekend a press release landed in my inbox, and I thought it interesting enough to make me contact the agency and get more information about the product. In summary ScaleArc iDB promised to scale your database without changes in code or database itself:
ScaleArc, the pioneer in a new category of database infrastructure that accelerates application development by simplifying the way database environments are deployed and managed, today announced general availability of iDB v2.0 for Microsoft SQL Server that brings significant new capabilities to SQL Server environments such as instant horizontal scaling, higher availability, faster database performance, increased SQL protection and real-time query analytics. iDB takes a fundamentally different approach at the SQL protocol layer by providing customers with a wide spectrum of capabilities for their database environment in a single solution, without requiring any modifications to existing applications or SQL Server databases.
Until now, moving to advanced architectures like multi-master, or achieving instant scale and better performance within SQL server environments, has been costly and extremely difficult to implement. iDB v2.0 for MS SQL supports a wide range of functions including Read/Write splitting, dynamic load balancing and horizontal scaling, query caching for up to 24x faster query responses, wire-speed SQL filtering and real-time instrumentation and analytics to enhance all deployment modes of SQL server, including SQL Server Clustering, SQL mirroring, Peer-to-Peer (P2P) Replication and log shipping.
iDB for MS SQL Feature Highlights
. Dynamic Query Load Balancing for High Availability: ScaleArc iDB implements a specialized dynamic load-balancing algorithm that allows the most efficient utilization of available database capacity, even when servers have varying capacity. iDB monitors query responses in real-time and can load balance queries to the server that will provide the fastest response to properly distribute the load. Up to 40% better performance has been observed with iDB's dynamic load balancing relative to TCP-based load balancing.
. Pattern-Based Query Caching for Increased Performance: ScaleArc iDB allows users to cache query responses with one-click. No changes are required at the database server or in the application code; the query is cached at the SQL protocol level, providing up to 24x acceleration without any modifications.
. Multi-master: iDB supports multi-master and master-slave scenarios to ensure high availability and scalability. Specific queries, irrespective of their origin, are routed to the right server with the advance query routing engine that also simplifies sharding.
. Real-time Analytics: Advanced graphical analysis tools provided by ScaleArc iDB bring comprehensive real-time awareness of all queries, helping to quickly pinpoint query patterns that are not performing optimally and allowing more precise management.
. Wire Speed SQL filtering: iDB is able to enforce query-level policies for security or compliance reasons to protect against attacks, theft and other threats. iDB can operate outside of the application where policies have not traditionally been easily enforced.
. SQL Query Surge Queue: Extreme loads can lead to unacceptable response times or even halting of operations until the load reduces, leading to "Database not Available" errors. ScaleArc iDB allows a more graceful response to peak loads. When faced with an extreme load, ScaleArc iDB can initiate a SQL Query Surge Queue and momentarily queue queries in a FIFO queue and process them once server resources become available.
Obviously I was a bit worried with their claims, so asked a couple of questions. Here are the answers:
What happens to cached query results when the result changes? For example a record is updated - will the next query use previous results, or get new results?
The key to iDB lies in our Analytics. We provide granular real-time data on all SQL queries flowing between application servers and the database servers. As such, customer now have the intelligence they need to understand the query structure, the frequency it hits the database, the amount of server resources it takes, etc. We then give the customer the power to cache on a per query basis, but we do not set a Time-To-Live for the customer. They need to understand how often the query will be updated, and ensure they do not set a Time-To-Live that may serve stale data is an Update comes in from the Application. We allow customers to set TTL anywhere from 1 second to multiple years. When a cache rule for a query is activated with a single click of a button, we immediately measure the performance and offload impact of the cache. And since our cache on iDB is a hash map that caches the TCP output of Read queries, subsequent Read queries served from our cache are served up to 24x faster (or more).
ScaleArc also has API that can be invoked from the application to add, invalidate and bypass the cache for specific SQL statements
How much more memory does it require? Or does it use the SQL DB footprint?
ScaleArc iDB is a Network appliance like deployment and does not have any agents on the Server or the Application.This would mean that iDB has its own physical/virtual machine to perform its operations. iDB can run load balancing within 4GB of memory, however for caching and logging purposes iDB can address up to 128GB of memory.
iDB is a separate instance from the database. Most customers run our software on a dedicated x86 server to make it a dedicated appliance. We also sell appliances, or iDB can be installed on a hypervisor as a Virtual Machine. iDB does not require a lot of memory to operate, but we can allocate up to 128GB of RAM for caching of READ queries. Query logs are stored on drives on the appliance.
Very interesting - an appliance for SQL TCP output caching. Ok, I have entered my name in to get a 30 day trial and see how much difference it can actually make.
UPDATE: Someone on Facebook said this was advertising. IT IS NOT. I was not asked to post about it, and did not receive any payment to post about it. If you are so inclined please read my FULL DISCLOSURE post.
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