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RStor launched in 2018 with a proposition that challenged the idea of putting every dataset and workload in one public cloud or data center: coordinate storage and compute across public clouds, enterprise facilities and supercomputers, then use a specialized network fabric to reduce the cost of distance. Cisco Investments led a reported $45 million funding round, but Cisco’s share was not disclosed and the performance claims came from the company rather than an independent benchmark. PacketFabric announced its acquisition of RStor in 2021; that announcement described an intended integration, not a confirmed standalone product that is still sold today.
What was RStor?
RStor was a Saratoga, California-based infrastructure startup that emerged from stealth in April 2018 with the RStor Multicloud Platform. Its premise was that no single location consistently offers the best combination of price, performance, capacity, data locality and specialized hardware.
RStor founder and CEO Giovanni Coglitore summarized that premise this way: “We don’t believe there’s a single location that has everything that you possibly need and the best possible configuration.” The platform was presented as a way to select resources wherever they were most suitable instead of treating one cloud or one facility as the default home for every workload.
The launch report described two ways to use the system:
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- Save valuable floor space: 6U wall mount server cabinet Dimensions: 13.78" H x21.65" W x17.72" D.Maximum mounting depth is 14.2"
- Keep critical network equipment secure: glass door and side panels are lockable to prevent unauthorized access. Front door can be installed on either side of the front of the cabinet to satisfy your door swing orientation preference
- Easy equipment configuration: Fully adjustable mounting rails and numbered U positions, with square holes for easy equipment mounting with top and bottom punch-out panels for easy cable access
- Durability: Made of high quality cold rolled steel holds up to 110lb (50kg) (Easy Assembly Required)
- PCI & HIPPA and EIA/ECA-310-E compliant
- Place information in RStor’s distributed Data Lake, hosted across colocation facilities and connected to cloud and supercomputer resources.
- Leave information where it already resides and run compute against it remotely, avoiding a full copy into RStor’s lake.
Coglitore described the underlying fabric as one that “stitches together the world’s cloud service providers and supercomputer centers.” Those were launch-era descriptions and aspirations, not an independent assessment of a generally available service.
How was the architecture supposed to work?
Distributed storage
The Data Lake model spread data across RStor-connected colocation sites while exposing connections to external clouds and high-performance computing centers. In principle, that arrangement could let an organization keep frequently used or location-sensitive data near the resources that process it, while still presenting a coordinated data layer.
Compute where the data already lives
RStor also described a remote-compute path. Instead of moving a large dataset into a new repository, an application could execute against data held in another connected location. That distinction matters for workloads where moving terabytes is slower, more expensive or less acceptable than moving computation.
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The company said its fabric was designed to reduce WAN overhead, congestion and packet loss. The report attributed use of Remote Direct Memory Access (RDMA) and proprietary protocol extensions to RStor, but the interview did not disclose enough implementation detail to independently evaluate the design, its interoperability or its operational limits.
What latency did RStor claim?
Data Center Knowledge’s April 26, 2018 report quoted Coglitore as describing an 80-millisecond round trip between the US West Coast and East Coast—about 40 milliseconds each way. The same article compared that with roughly 60 milliseconds one way between opposite-coast AWS availability zones.
These figures should be read narrowly. The 80-millisecond number was a company-reported figure in a launch interview, while the AWS number was the article’s contemporaneous comparison. Neither is a controlled, independently verified benchmark, a current latency guarantee or a promise for every route, carrier, workload or time of day.
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- Save valuable floor space: 12U wall mount server cabinet Dimensions: 24.25" H x21.65" W x17.72" D. MAXIMUM MOUNTING DEPTH is 14.2".
- Keep critical network equipment secure: glass door and side panels are lockable to prevent unauthorized access; Front door can be installed on either side of the front of the cabinet to satisfy your door swing orientation preference
- Easy equipment configuration: Fully adjustable mounting rails and numbered U positions, with square holes for easy equipment mounting with top and bottom punchout panels for easy cable access
- Durability: Made of high quality cold rolled steel holds up to 110lb (50kg) (Easy Assembly Required)
- PCI & HIPPA and EIA/ECA-310-E compliant
What did Cisco invest in?
The 2018 report said Cisco Investments led a $45 million RStor funding round. Michael Porat, a Cisco Investments director, did not disclose Cisco’s portion. The report also corrected an earlier account that had stated Cisco invested $80 million and was RStor’s sole investor; that $80 million figure should not be treated as the funding amount established by the launch report.
Porat characterized the investment as early-stage. His comments focused on the team and the customer problem rather than on one specific technology component. He also said, “The premise that everything is going to be in AWS is pretty much outdated.” In the same interview he cautioned, “It’s early days,” a useful qualification for interpreting both the product description and Cisco’s bet.
Where was RStor’s network?
According to Coglitore, the fabric used Equinix facilities in Ashburn, San Jose and the United Kingdom, along with a CoreSite facility in Los Angeles. The company said expansion into Hong Kong, Singapore and Brazil was in progress. These were locations and plans reported in 2018, not a verified current footprint.
What workloads did the idea target?
The platform’s selection logic was described as balancing performance and cost when choosing compute resources. The architecture could be relevant to organizations that have unusually large datasets, access to specialized supercomputers, geographically distributed operations or reasons to keep data in a particular facility.
The launch report mentioned one unnamed pharmaceutical customer using remote compute on data, based on Coglitore’s account. It did not identify the customer or provide an independent validation of the deployment, so the example demonstrates the intended use case rather than a measured reference result.
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RStor’s proposal raises practical trade-offs that apply to any distributed data-and-compute design. They are decision criteria, not advantages that RStor independently proved.
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- Sturdy:4u server rack is construct from cold rolled steel, with a weight capacity of 110lbs(50kg); Electrostatic powder coat prevents rust and corrosion,quality finish
- Direct use:Open and use, not having to assemble it.Network rack can be placed flat or mounted on the wall,also can be installed vertically under the table
- Design Features:maximum mounting depth of 14 in,cables can be fixed on the side panel;Open frame server rack achieves effortless inspection, replacement and assemble
- Installation:wall mount network rack is easy to install,with instructions or videos for reference;Equipped with multiple accessories, suitable for different needs
- Application:EIA/ECA-310-E Compliant;wall mounted 4u rack fits all 19" racks and cabinets to hold various IT, network, and AV equipment;wall mount rack available in 4U, 6U, and 8U to choose
| Question | Why it matters |
|---|---|
| Where should data reside? | Physical and regulatory location, replication policy, access patterns and egress charges can outweigh the appeal of a single logical data layer. |
| Where should compute run? | CPU, GPU, memory, accelerator and software requirements may differ by workload; a remote site is useful only if it can run the required stack. |
| How much data must move? | Remote execution can avoid bulk transfers, but applications still exchange requests, intermediate results and metadata across the network. |
| What latency and loss can the application tolerate? | Network distance, congestion, packet loss and protocol behavior affect interactive transactions differently from batch analytics. |
| What will it cost? | Storage, compute, interconnection, transfer, replication and operations costs need to be modeled together rather than compared as a single cloud-rate line item. |
| What controls are required? | Identity, encryption, isolation, auditability and jurisdictional rules must hold across every participating cloud, colocation site and supercomputer facility. |
What happened to RStor after the launch?
On October 4, 2021, PacketFabric announced that it had acquired privately held RStor. PacketFabric said it intended to integrate RStor’s storage infrastructure and data-mobility technology at the edge of its carrier-class network-as-a-service platform.
PacketFabric CEO Dave Ward described the intended benefit as follows: “By integrating RSTOR’s storage infrastructure and data mobility technology at the edge of PacketFabric’s carrier-class Network as a Service platform, we can help enterprises build an agile and high-performance cloud data core.” That sentence states the rationale for the acquisition; the announcement does not independently establish achieved performance.
The available documentation confirms the acquisition announcement and its planned direction. It does not establish the resulting product’s name, packaging, customer availability, or whether a standalone RStor service remains available. Organizations looking for the technology should therefore verify current offerings and support directly with PacketFabric rather than assume the 2018 RStor platform can still be purchased unchanged.
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Why the RStor thesis still matters
RStor’s launch captured a lasting infrastructure question: should data and compute be centralized by default, or coordinated across the places that best fit each workload? Public clouds, enterprise sites, colocation facilities and supercomputers have different economics, hardware and governance constraints. A networked data layer can be compelling when moving the data is the dominant cost or delay, but it also introduces dependencies across providers and locations.
The historical record supports RStor as an early, Cisco-backed attempt to address that problem. It does not support treating the launch claims as a current benchmark, a universal architecture or proof that the proposed fabric delivered a particular business outcome.
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