I recently had the opportunity to speak to Victoria Grey (CMO) and Jonathan Calmes (VP Business Development) from Aparavi regarding some updates to their Active Archive solution. If you’re a regular reader, you may remember I’m quite a fan of Aparavi’s approach. I thought I’d share some of my thoughts on the announcement here.
According to Aparavi, Active Archive delivers “SaaS-based Intelligent, Multi-Cloud Data Management”. The idea is that:
- Data is archived to cloud or on-premises based on policies for long-term lifecycle management;
- Data is organised for easy access and retrieval; and
- Data is accessible via Contextual Search.
Sounds pretty neat. So what’s new?
Direct-to-cloud provides the ability to archive data directly from source systems to the cloud destination of choice, with minimal local storage requirements. Instead of having to sotre archive data locally, you can now send bits of it straight to cloud, minimising your on-premises footprint.
- Now supporting AWS, Backblaze B2, Caringo, Google, IBM Cloud, Microsoft Azure, Oracle Cloud, Scality, and Wasabi;
- Trickle or bulk data migration – Adding bulk migration of data from one storage destination to another; and
- Dynamic translation from cloud to cloud.
[image courtesy of Aparavi]
The Active Archive solution can now index, classify, and tag archived data. This makes it simple to classify data based on individual words, phrases, dates, file types, and patterns. Users can easily identify and tag data for future retrieval purposes such as compliance, reference, or analysis.
- Customisable taxonomy using specific words, phrases, patterns, or meta-data
- Pre-set classifications of “legal”, “confidential”, and PII
- Easy to add new ad–hoc classifications at any time
Advanced Archive Search
Intuitive query interface
- Search by metadata including classifications, tag, dates, file name, file type, optionally with wildcards
- Search within document content using words, phrases, patterns, and complex queries
- Searches across all locations
- Contextual Search: produces results of the match within context
- No retrieval until file is selected; no egress fees until retrieved
I was pretty enthusiastic about Aparavi when they came out of stealth, and I’m excited about some of the new features they’ve added to the solution. Data management is a hard nut to crack. Primarily because a lot of different organisations have a lot of different requirements for storing data long term. And there are a lot of different types of data that need to be stored. Aparavi isn’t a silver bullet for data management by any stretch, but it certainly seems to meet a lot of the foundational requirements for a solid archive strategy. There are some excellent options in terms of storage by location, search, and organisation.
The cool thing isn’t just that they’ve developed a solid multi-cloud story. Rather, it’s that there are options when it comes to the type of data mobility the user might require. They can choose to do bulk migrations, or take it slower by trickling data to the destination. This provides for some neat flexibility in terms of infrastructure requirements and windows of opportunity. It strikes me that it’s the sort of solution that can be tailored to work with a business’s requirements, rather than pushing it in a certain direction.
I’m also a big fan of Aparavi’s “Open Data” access approach, with an open API that “enables access to archived data for use outside of Aparavi”, along with a published data format for independent data access. It’s a nice change from platforms that feel the need to lock data into proprietary formats in order to store them long term. There’s a good chance the type of data you want to archive in the long term will be around longer than some of these archive solutions, so it’s nice to know you’ve got a chance of getting the data back if something doesn’t work out for the archive software vendor. I think it’s worth keeping an eye on Aparavi, they seem to be taking a fresh approach to what has become a vexing problem for many.