Exponential data growth takes a toll on your backup storage budget. Up until now, data deduplication relied on hardware appliances or was tied to only one vendor’s backup solution.
Quest® QoreStor® provides a pure software solution that you can run on-premises or in the cloud and use with most backup solutions. QoreStor’s source-side data deduplication with built-in compression delivers unparalleled storage savings — up to 95%.
Many IT professionals seek a specialized deduplication appliance that supports their backup solution, but appliances have challenges and limitations. The QoreStor software-defined deduplication solution has many advantages over purpose-built appliances.
To start, it can be run on the hardware or virtual machine (VM) you prefer. You can run it in the data center, any remote site, and in public clouds like AWS, Azure, and Google. And since it’s software, you don’t have to pay for it over and over as you would for an appliance as you go through hardware refresh cycles.
QoreStor not only provides unparalleled deduplication results, but you also get built-in backup acceleration, replication and cloud connectors for disaster recovery and long-term data retention.
Fixed-block deduplication has many challenges and delivers sub-par performance. QoreStor’s sliding window, variable block deduplication has many advantages.
Because the data is variable and is calculated over a sliding window, that same set of bytes of data (variable chunks of data) can be identified again and again, no matter where it is in the stream of data. This prevents the need to have the data nicely aligned to catch duplicates, which is required with fixed-block dedupe systems.
Overall, variable-block deduplication provides more matches. This reduces the amount of unique data that has to be stored and results in saving significantly more storage space than other dedupe technologies.
QoreStor adds a content-aware algorithm to its variable-size chunking. The algorithm identifies patterns in the data in spite of the shifting that results from additions or deletions in the data stream. It then aligns the block starting points and endpoints to duplicate chunks, while identifying only the changed chunks as unique.
This unique approach combined with built-in compression delivers the best possible deduplication results – up to 95% storage savings.