Analyst Coverage
Laura DuBois, Research Director, IDC
Over the last few years, data has ballooned in enterprises to staggering proportions, and the need to classify and manage it has grown as a result. It is not at all unusual for IT to be expected to manage terabytes of data. Abrevity’s distributed solution is ideal for addressing such massive amounts of data enabling them to succeed at this prodigious task.
Michael Karp, Senior Analyst, Enterprise Management Associates
If you can’t see or find data, you just can’t manage it. Today enterprises are required to manage data located in diverse remote locations just as though it were contained on a single disk drive at one central location. Only products like Abrevity can provide both the visibility and accuracy across multiple locations to accomplish acceptable data management scalability and performance.
Anne MacFarland, Director of Data Strategies and Information Solutions, The Clipper Group
Abrevity has offered an integrated data classification application and non-relational database built to support data classification on a large scale. Now, with version 3.0, Abrevity offers multi-threaded classifiers and a multi-node distributed form of their database. This supports distributed queries and transactional consistency across nodes, extends the concept of vast to prodigious dimensions, and gives enterprises, both large and small, more tools for optimizing the business and organizational value of their information.
Ray Lucchesi, President, Silverton Consulting
Data classification products like Abrevity bring new management capabilities to the file data domain. Abrevity has taken the next logical step to create a more scalable/distributed classification engine architecture to address the massive file data management needs of enterprise class customers. Abrevity can scale to address the more extreme performance requirements as well as absolute capacity needs of the large enterprise customer.
Vivian Tero, Senior Research Analyst, IDC
Today’s enterprises are faced with a growing need to find regulatory audit and legal discovery data quickly and accurately. Searching and finding potential responsive evidence through terabytes of geographically-dispersed data under the new eDiscovery Rules timeline can be a daunting task. There is a need for solutions that automate this process while scaling up effectively to match the data volume growth and providing acceptable performance results. Abrevity’s 3.0 release is intended to address this need.
David G. Hill, Principal, Mesabi Group
Managing data means finding it, and finding and managing all that distributed data in today’s enterprises is a complex problem. Not only is data stored in geographically disbursed locations, like remote offices, but managing that from in a centralized way can be an even more cumbersome problem. Fortunately, sophisticated data management solutions like Abrevity’s provide the right balance of automation and ease of use to allow data to be found no matter where it’s located.
Dan Tanner, Analyst, ProgresSmart
Purchasing storage in an ad hoc manner as data expands is self-defeating. As such, a tiered-storage approach is being mandated by most organizations in order to achieve rational ILM. However, because of the complexities involved, many enterprises are struggling with the logistics of implementing a comprehensive ILM strategy. The introduction of an appliance, such as the ATS, promises to address the problem in a very manageable and rational way.
Heidi Biggar, Analyst, Enterprise Strategy Group
IT professionals are looking for tools that provide increased ‘visibility’ into their growing data stockpiles. They are looking for ways to sort out what they have and then leverage this information for business purposes. Abrevity is one of a growing number of vendors taking steps to provide this type of view of data. What differentiates Abrevity from the pack is its use of a new data model (versus conventional relational database or enterprise search technologies) to enable fast search, discovery, and data analysis of the large data volumes being generated today.
