Global digital consulting firm JK Tech is seeking to improve enterprise AI data insights with the launch of its Google-driven JIVA platform.
The generative AI (Gen AI) technology promises improved data accessibility, while “notably enhancing” precision and minimizing hallucinations – a common challenge when using traditional large language models. JK Tech has implemented Gen AI in the automotive insurance sector where, for example, Gen AI chatbots can help handle initial claim registration, which reduces claim handling time by up to 50 percent. This helps both the insurer, which can handle more claims in less time, and the policyholder, who receives their payout faster.
Using “advanced” Gen AI technologies, JIVA uses Google’s Knowledge Graph and other tools to construct a dynamic interconnected graph that fosters traceability and contextual comprehension.
Dipankar Ganguly.
The in-context training and reasoning engine within JIVA facilitates “deeper understanding,” leading to more accurate conclusions. The Nodal Level Security is a “unique feature” of JIVA, claims the Noida, Uttar Pradesh, India-headquartered provider. It integrates enterprise access management, ensuring secure data access, and mitigating the risk of data misinterpretation.
“As organizations continue to navigate the complexities of digitization, data has become a critical asset for strategic decision-making and driving innovation,” explained Dipankar Ganguly, chief technology officer of JK Tech. “We believe in unleashing the full potential of Gen AI in the digital transformation journey of businesses. Through in-depth discovery sessions, we work with clients to identify key areas where Gen AI can deliver tangible value.”
The offer includes customization and integration tailored to specific needs, end-to-end training, and “seamless” implementation.
“Through our ongoing support and optimization services, we remain committed to keeping our customers’ Gen AI initiatives innovative, and leading the way in the evolving business environment,” declared Ganguly.
JK Tech’s market sweet spots are retail and consumer products, insurance, financial services, and healthcare industries – all verticals that are big on trying to make AI work in a meaningful way.
Bloomberg reported over Easter that Rubrik is prepping an IPO and could file papers with the SEC this week.
This follows a Reuters report in February that the Bipul Sinha-led business was planning an April 2024 IPO once a fraud investigation completed. Bloomberg previously suggested that Rubrik could IPO by the end of last year.
Bipul Sinha.
Rubrik started up in 2014 as a backup and restore-based data protector, and has evolved to add cyber security and resilience. This has become its main focus. The founders were ex-venture capitalist and CEO Bipul Sinha, CTO Arvind “Nytro” Nithrakashyap, VP engineering Arvind Jain and Soham Mazumdar. It has raised in excess of $550 million – possibly as much as $1 billion – with a valuation thought to be in the $4 billion area when Microsoft invested in 2021. The firm reckons it has more than 5,000 customers and in excess of $600 million in annual recurring revenue. Previous reports have identified Goldman Sachs, Barclays and Citigroup as its IPO bankers.
The Bloombergers guess that Rubrik could raise $500 million to $700 million from this IPO. A Rubrik IPO would represent a pinnacle of achievement for Bipul Sinha, who was born into poverty in India.
The Information reported two other cyber security vendors – Snyk and Cato Networks – could also run IPOs this year.
Arch rival Cohesity, which filed for an IPO in December 2021, is acquiring the bulk of the business from legacy data protector Veritas and plans for an IPO to follow that in due course. This acquisition could make it a larger business – in terms of revenue and customer count – than Rubrik.
Social media platform Reddit and semiconductor supplier Astera have both successfully launched IPOs recently, providing a generally positive investor environment.
Enterprise data management vendor Starburst, which bills itself as “the open lakehouse,” has brought in a number of seasoned data veterans to help it scale up.
Steven Chung has been named as president, Tobias Ternstrom is now chief product officer, and Adam Ferrari has been brought in as senior vice president of engineering.
Starburst’s exec trio of hires. Left to right: Adam Ferrari, Steven Chung, and Tobias Ternstrom.
“Steven, Tobias, and Adam have joined our team, inspired by our vision to help organizations unlock greater business value from their data through the Starburst Lakehouse platform,” declared Justin Borgman, co-founder and CEO of Starburst.
“The appointment of these industry leaders will help scale our business globally,” added Mike Volpi, Starburst board member and founding investor from Index Ventures. “Steven, Tobias, and Adam bring proven experience to Starburst as we power new opportunities with AI, ML, and analytics in cloud, on-prem, and in hybrid environments.”
Prior to Starburst, Chung served as president at Delphix, the enterprise DataOps biz that was recently acquired by Perforce Software. In addition, he has held senior executive roles at PagerDuty, Demandware, Symantec, Microstrategy, and PwC Consulting.
Ternstrom joins the party from Nutanix, where he served as vice president of platform services, bringing database-as-a-service to hybrid multi-cloud environments. Ternstrom’s other previous roles were at Amazon Web Services, Google Cloud Platform, and Microsoft. At AWS, Ternstrom led product management for Amazon Aurora and Amazon Relational Database Service (RDS).
Ferrari brings 20 years of engineering leadership, where he most recently served as SVP of engineering at Salsify – a leading product information management (PIM) provider. He has also led product and engineering teams at Oracle and Endeca (prior to its acquisition by Oracle in 2011).
Starburst says it offers a “full-featured,” open data lakehouse platform, built on open source Trino. Its end-to-end analytics include the capabilities needed to discover, organize, consume, and share data, with “industry-leading price-performance” for both cloud and on-premise workloads. The technology is used by end customers like Comcast, Grubhub, and Priceline.
Data protection outfit Rubrik is feeding data to CrowdStrike in a bid to improve its attack detection and response.
CrowdStrike’s Falcon XDR product ingests data from various security tool repositories across a customer’s IT estate and uses AI to help it hunt threats and respond to attacks. It has been involved in investigations of several high-profile cyberattack investigations, such as the 2014 Sony Pictures breach and the cyberattacks and email leaks at the Democratic National Committee.
The more data it has about IT estate activities, particularly those involving critical data, the better. Rubrik’s integration may well remove a blindspot from CrowdStrike’s threat hunting activities.
Anneka Gupta
Anneka Gupta, Rubrik chief product officer, said: ”The gap between threat detection, data discovery, and classification creates significant visibility challenges for security teams defending critical data. With CrowdStrike, we are helping our customers up the ante against cyber adversaries, allowing security teams to identify and defend against attacks swiftly – and ultimately boost cyber resilience.”
CrowdStrike’s chief business officer, Daniel Bernard, added: “Our partnership with Rubrik strengthens CrowdStrike’s data gravity, unifying threat detection with data discovery, classification and backup. Through this partnership, we’re delivering the visibility and context security teams need to prioritize and accelerate response actions required to stop breaches of sensitive information – all from a single platform.”
The company says it generates security telemetry and enriches it with adversary intelligence and human expertise via its Falcon platform. The Rubrik data feed to Falcon’s LogScale functionality provides data target indicators, particularly for critical data, aiding attack behavior characterization.
With the integration, Rubrik says customers can optimize security and IT operations, reduce alert fatigue, and better focus efforts on stopping data breaches.
Arch Rubrik rival Cohesity set up an integration with CrowdStrike and its Falcon LogScale dashboard in November last year as part of Cohesity’s Data Security Alliance activities. The Falcon LogScale and Cohesity DataHawk combo helps provide faster correlation, investigation, and response to incidents in one location. Cohesity said the CrowdStrike integration provides closed-loop detection and response for attacks directly within the CrowdStrike Falcon platform.
Rubrik Security Cloud for Falcon Logscale is available from today in the CrowdStrike Marketplace. Learn more at an upcoming webinar on Wednesday, April 24, at 2pm ET.
It says DBRX lets customers build, train, and serve their own custom LLMs more cheaply, without having to rely on a small set of closed models. Closed LLMs, like ChatGPT and GPT-3.5, are based on private model weights and source code whereas open source ones such as LlaMa, Dolly, and DBRX have publicly available source code and model weights.
Developers can inspect their model architecture and training data and customize the source code, according to Databricks.
Databricks co-founder and CEO Ali Ghodsi said: “We’re excited about DBRX for three key reasons: first, it beats open source models on state-of-the-art industry benchmarks. Second, it beats GPT-3.5 on most benchmarks, which should accelerate the trend we’re seeing across our customer base as organisations replace proprietary models with open source models. Finally, DBRX uses a mixture-of-experts architecture, making the model extremely fast in terms of tokens per second, as well as being cost effective to serve.”
A Databricks chart shows DBRX delivering results faster than other open source LLMs like Llama 2 70B and Mixtral-8x7B on industry benchmarks such as language understanding, programming, maths, and logic.
The MMLU (Massive Multitask Language Understanding) is a benchmark designed to measure knowledge acquired during pre-training by evaluating models exclusively in zero-shot (no labeled data available for new classes) and few-shot (limited number of labeled examples for each new class) settings. The benchmark covers 57 subjects across STEM, humanities, social sciences, and more. Programming (Human Eval) is a programming challenge dataset. Math GSM8K is a dataset of 8.5K high quality linguistically diverse grade school math word problems created by human problem writers.
The performance differences are minor on the MMLU test, significant on the Programming (Human Eval) run, and less significant on the Match (GSM 8K) benchmark/
DBRX also goes faster than GPT-3.5, according to claims from Databricks:
The pattern of performance differences is the same as with the open source chart above; minor on the MMLU test, significant on the Programming (Human Eval) run, and less significant on the Match (GSM 8K) benchmark.
Databricks says it has optimized DBRX for efficiency and with a mixture-of-experts (MoE) architecture, built on the MegaBlocks open source project. The MoE architecture is said to enable trillion parameter-class training with billion parameter-class compute resources. A Hugging Face blog explains the concept.
DBRX is claimed to be up to twice as compute-efficient as other available LLMs. Databricks says it can be used, when paired with Databricks’ Mosaic AI tooling, to build and deploy safe, accurate, and governed production-quality GenAI applications without customers giving up control of their data and intellectual property.
Mike O’Rourke, head of AI and Data Services at Nasdaq, said in a canned remark issued by Databricks: “Databricks is a key partner to Nasdaq on some of our most important data systems … and we are excited about the release of DBRX. The combination of strong model performance and favorable serving economics is the kind of innovation we are looking for as we grow our use of Generative AI at Nasdaq.”
DBRX is freely available on GitHub and Hugging Face for research and commercial use. Databricks is running a DBRX webinar on April 25, 1500 UTC. Check out a DBRZ article at its Mosaic AI Research blog.
Comment
Relying on a particular GenAI model’s speed at this early stage in development, on both hardware and software fronts, doesn’t appear to be a sustainable strategy unless you can afford to keep developing it at the same rate as the extremely well-heeled closed model developers.
Startup Observe has raised a $115 million B-round for its SaaS-based observability service following 171 percent ARR growth in its latest fiscal year.
Jeremy Burton
Observability and application performance monitoring (APM) software looks at applications – particularly cloud-native applications – and collects events and log data, activity metrics, component service invocations, and results. Observe adds meaningful business context to the raw basic data – such as customers and users, a shopping cart, a Kubernetes pod, a software build identifier, a problem ticket, and so forth. It brings this data to a single Snowflake repository and uses elastic cloud features for its analysis compute and capacity, helping issues get identified, understood, and fixed faster.
CEO Jeremy Burton explained: “Legacy monitoring and APM players, shackled by outdated architectures, are dead companies walking. As private equity or strategic acquirers strip them down for parts, Observe is taking a new approach designed for today’s modern distributed applications and massive data volumes. We’re thrilled to have investors who are thinking big and validating Observe’s approach in one of the fastest-growing segments in tech.”
A Gartner magic quadrant named the leading observability and APM vendors in 2023 as Dynatrace, Datadog, New Relic, Splunk, and Honeycomb. There were 14 other vendors mentioned in the MQ, but not startup Observe – it hadn’t registered with the Gartner analysts. Cisco has acquired Splunk while private equity buyers took Sumo Logic and also New Relic. The latter was bought by Francisco Partners and TPG at an equity valuation of about $6.5 billion.
Observe’s new investors include Sutter Hill Ventures, which led the round, and existing investors Capital One Ventures and Madrona plus a marquee new investor: Snowflake Ventures. They all put in the cash valuing Observe ten times higher – $325 million as we understand it – than the company’s $35 million Series A round four years ago. That included contributions from Michael Dell, Snowflake CEO Frank Slootman, and Pure CEO Scott Dietzen.
Observe funding history:
2017 – founded
2020 – $35 million A-round
2021 – $7 million venture round
2022 – $70 million A2 round
2024 – $115 million B-round
Total funding: $227 million
Recent growth stats are what pleased investors:
New average contract value (ACV) increased 176 percent year-over-year in FY24
Total Contract Value (TCV) increased 194 percent in FY24
Net Retention Revenue (NRR), which indicates stickiness of product, is 174 percent (industry-leading is considered 130 percent)
Mike Speiser, MD at Sutter Hill Ventures and a founder of Observe, elaborated: “Observe has … delivered a product that is architecturally different to everyone else. The incredible growth in ARR and NRR is testament to the fact that this new architecture is now paying off for their customers.”
Customers include Capital One, Reveal, and Top Golf. Mark Cauwels, managing VP, enterprise platforms technology at Capital One, provided a canned blurb: “Like many cloud-first organizations, our data volume continues to expand. Observe provides a centralized and pre-correlated data layer that meaningfully organizes telemetry data from many sources at scale, helping drive faster response times.”
Observe’s headcount increased more than 50 percent year-over-year and the biz is growing its sales organization, planning to expand its market presence in North America over the coming year. It expects to more than double the size of its business.
DataStax has integrated with Microsoft’s Semantic Kernel to help developers build retrieval-augmented generation (RAG) applications and vectorize data with Astra DB and Semantic Kernel’s extensible open source SDK for AI applications and agents. Any C#, Python, or full-stack application developers can build RAG apps and AI agents for their enterprise data using Semantic Kernel’s features for managing contextual conversations, multi-step functions, and connections with the Microsoft AI ecosystem. Semantic Kernel lets developers build agents that can call to existing code and be used with orchestration models like OpenAI, Azure OpenAI, GitHub Copilot, and Hugging Face. Key features of Semantic Kernel include semantic functions, chaining capabilities, planners, and connectors for various enterprise applications and data sources.
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Data lakehouse supplier Dremio announced general availability of Dremio Cloud on Microsoft Azure, claiming lakehouse flexibility, scalability, and performance at a fraction of the cost of traditional data warehouses. Dremio Cloud on Azure dynamically and automatically optimizes resources and capacity based on usage. It has end-to-end TLS encryption and no customer data resides within the Dremio environment. Customers can control their data within their own Azure tenant, in storage services such as Azure Data Lake Storage (ADLS).
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FileShadow is a SaaS service that connects user content from wherever those files are located – cloud storage, email, mobile devices, hard drives etc. – to a FileShadow Library. It can be used on a desktop, a browser, or a mobile device, and users can share their content with others through it. FileShadow has announced person detection and object identification in user images, allowing them to tag individuals (or other objects). It can help photographers organize images of a shoot, group images associated with an event, and label names of buildings or animals.
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InterSystems has added vector search to its IRIS data platform to enhance its functionality for natural language processing (NLP), text, and image analysis tasks. This capability allows the IRIS software to manage and query content and related dense vector embeddings – particularly as it enables RAG integration to develop generative AI-based applications.
Michael Sotnick
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Cloud file services supplier Nasuni has appointed Michael Sotnick as its SVP of business and corporate development. He joins Nasuni from Pure Storage, where he served as the VP of alliances and business development for eight years. Sotnick assumes responsibility for Nasuni’s global partnerships including Microsoft Azure, Amazon Web Services, and Google Cloud, and will also drive new strategic technology partnerships.
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According to a source, a visiting NetApp senior exec told people at an Australian event last week that Dell could offload its storage business. Both Dell and NetApp declined to comment when asked.
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Nvidia’s AI Enterprise software platform is generally available. It includes microservices such as NIM to speed up Gen AI application deployments, cuOpt for routing problems, and AI Workbench to create, test, and customize pre-trained Gen AI models and LLMs on a PC or workstation and infrastructure management enhancements. Check out the announcement blog for more information.
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Media workflow NAS supplier OpenDrives has a forthcoming Atlas product and workflow-centric business model to be unveiled at NAB 2024 in Las Vegas, April 13–17. It will let Atlas customers adjust their capabilities based on their creative workflow requirements, with a straightforward process for upgrading or downgrading.
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Samsung unveiled the expansion of its Compute Express Link (CXL) memory module portfolio and showcased its latest HBM3E technology at Memcon 2024 in Santa Clara, California. It introduced its CXL Memory Module – Box (CMM-B), a CXL DRAM memory pooling product that can hold 8x CMM-D E3.s devices and provide up to 2TB of capacity with up to 60GB/sec bandwidth and 596ns latency.
A CXL Memory Module – DRAM (CMM-D) technology, validated with Red Hat, has DRAM integrated with CXL to facilitate connectivity between an x86 CPU and memory expansion devices. Samsung also demonstrated its HBM3E 12Hi chip.
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SIOS LifeKeeper Web Management Console screenshot
High availability supplier SIOS has a new web console for its LifeKeeper for Linux product. LifeKeeper protects apps such as SAP HANA, Oracle, and others from downtime and disasters. The LifeKeeper Web Management Console (LKWMC) features:
Simplified processes and intuitive interfaces to save time and reduce errors in configuration and ongoing management;
Set up Progress Tracking to monitor the installation process in real time;
Self-Help “Information Cues” simplifying configuration and management;
Self-Contained system simplifying the deployment process and reduces maintenance overhead, with no need for Java or X Window System installation on the server;
Language localization support initially available in both Japanese and English;
Simplified firewall management requiring only two TCP ports;
Access and functionality across a range of devices, including tablets and smartphones;
Support for leading platforms, operating systems, and enhanced SAP integration.
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SMART Modular Technologies introduces its ultra-high reliability memory solution, Zefr ZDIMM memory modules, offered in both DDR4-3200 and DDR5-5600 form factors and available in mainstream densities. “The industry standard for defective parts per million, or DPPM, for DRAM modules is in the 3,000 to 5,000 range,” said Tom Quinn, SMART’s SVP of business development. “Typical Zefr ZDIMM module DPPM ranges from 200 to 300. This ultra-high reliability is valuable in critical data processing environments where uptime is paramount and downtime costs can quickly escalate.” Learn more at DDR4 ZDIMM and DDR5 ZDIMM microsites.
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SQream, which supplies a scalable GPU data analytics platform, and Qantm AI, an advisory service for AI strategy, AI governance, and AI architectures, have announced a collaboration to provide SQream’s technology to Qantm AI’s customers.
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StorPool Storage was named as one of Europe’s fastest-growing companies according to a Financial Times report, which ranked organizations by the highest compound annual growth rate in revenue between 2019 and 2022. The biz was 842 on the list, with a CAGR of 42.4 percent during the time period. StorPool was one of only 147 tech companies in the survey – and the only company from Bulgaria – to be ranked in each of the past three years.
Rick Scurfield
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Synology says its Active Backup and C2 Backup offerings have achieved a milestone, safeguarding over 20 million SaaS user accounts, endpoints, servers, and VMs worldwide.
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VAST Data has appointed its first CRO: Rick Scurfield, who comes after a short break from being NetApp’s chief commercial officer. Scurfield, who spent 20-plus years at NetApp, takes over sales from VAST president Mike Wing.
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UK-based channel-first cloud and DR specialist VirtualDCS has launched CloudCover Guardian for Azure, powered by Veeam, which it claims is the world’s most comprehensive Azure backup service, protecting more than 250 configurable items in an established Microsoft 365 estate. It’s an alternative to Keepit, OwnBackup, and other Microsoft 365 SaaS backup services. CloudCover 365 offers more backup time slots than any other Microsoft 365 Backup solution in the market, where organizations can backup and protect data up to 12 times a day, providing a two-hour RPO window for business-critical data.
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Western Digital has spread its 24TB HDD technology to its Red Pro NAS drives. The Red Pro has a 2–24TB capacity range, a 550TB/year workload, 600,000 load/unload cycles, 2.5 million hours MTBF, 6GB/sec SATA interface, 7,200rpm spin speed, 287MB/sec sustained transfer rate at the 24TB capacity level, and OptiNAND technology with iNAND UFS embedded flash drive for 20, 22, and 24TB capacities.
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XConn Technologies announced the release of early production samples for its “Apollo” CXL 2.0 switch. It says the Apollo switch is the industry’s first and only hybrid CXL 2.0 and PCIe 5 interconnect product. On a single 256-lane SoC, the XConn switch offers the industry’s lowest port-to-port latency and lowest power consumption per port in a single chip at a low total cost of ownership. XConn’s Apollo will be the central component of a real-world use case demonstration of a CXL Memory Pool with Samsung during MemCon 2024, March 26–27, in Mountain View, California.
Syniti is a structured data lifecycle management supplier – with a focus on enterprise applications such as SAP and Salesforce – and not a file lifecycle management supplier.
As such, it occupies a different market sector from vendors such as Komprise, Datadobi, and Data Dynamics, whose focus is on unstructured file and object data and migrating it to lower-cost and slower storage as access rates diminish, not structured database record data. Yet the need for structured data lifecycle management is just as obvious as the need for file lifecycle management – possibly more so, as enterprise apps are often mission-critical with data placed in fast-access primary storage silos.
Syniti – like Komprise, Datadobi, and Data Dynamics – is a metadata scanning supplier, but its niche is enterprise app database metadata, with aspects related to business, technology, and application, rather than to file and object metadata.
Private equity-owned Syniti was founded in Boston in 1996 by Tom and Trish Kennedy as BackOffice Associates – an SAP-focused consultancy. BackOffice Associates developed information governance, data stewardship, and data migration software, such as its Syniti Knowledge Platform, for SAP, Oracle, and other ERP vendors.
Goldman Sachs invested in the business in 2011. In 2017, a majority stake in BackOffice Associates, with a $300 million valuation, was acquired from Goldman Sachs by private equity business Bridge Growth Partners. As a curiosity, ex-EMC CEO, chairman, and president Joe Tucci is a Bridge Growth Partners co-founder and chairman, and joined the BackOffice Associates board at the time. The BackOffice Associates name gave way to Syniti after this acquisition.
According to Bloor Research, Syniti now sells packaged cloud-native data management software “with about a third of its revenue coming from licenses rather than professional services.” Its more than 500 customers include American Airlines, Kraft, and Nestlé, and it has worked for more than 200 Forbes Global 2000 organizations. The business employs over 1,400 staff.
It has built more than 160 connectors to enterprise applications, with SAP a strong focus, meaning it can read and understand their metadata. This expertise is not something easily gained, and this is what partially prevents Komprise, Datadobi, and similar file-focused lifecycle management vendors moving into the structured data lifecycle world. This barrier works both ways: Syniti cannot easily move into the unstructured data lifecycle management market.
Chris Gorton
Syniti’s EMEA MD, Chris Gorton, told us in a briefing that one of Syniti’s first activities in a customer engagement is rightsizing. “For every application, [we ask] how have you managed that over time? The answer is typically ‘we haven’t.'”
This results in over-provisioned primary storage, with Gorton arguing: “There are SAP systems out there that are 60–70 terabytes. And when we do an initial assessment, we normally find that maybe six or seven terabytes of that is actually real operational data that they access.”
What is a typical trigger for customers to engage with Syniti? Gorton explained: “Because the technology vendors push them in that direction, because of the way they they acquire ERP software. It’s consumption-based. So they have to think, ‘well, hang on a minute, if I’m going to be charged on a consumption-based model, are we going to be storing and accessing data in the most efficient way?’ So, in a way, the ERP industry is forcing customers to be more cost-efficient.”
Syniti is not typically used as a one-shot exercise by its customers. It supports the view that data lifecycle management is an ongoing activity. Applications come and go, experience upgrades, move from the on-premises to the public cloud, and some get decommissioned. Data needs governance to make sure only the right people and apps can access it, and its retention meets compliance and privacy regulations. The data accumulated by decommissioned apps needs to be evaluated and, where appropriate, stored and made available to upstream apps.
This is another point of difference with file-based lifecycle management vendors: app decommissioning is not typically one of their focus areas.
Gorton explained that Syniti’s offerings are somewhat like IT plumbing. Syniti doesn’t, as we understand it, own the data. It provides data management and delivers data access to where it’s needed. For example, Gorton told us Syniti doesn’t see itself providing any GenAI-type copilots to analyze data. It sees its responsibility as delivering valid, cleaned, and compliant data to AI apps for them to analyze and process.
AI’s results, he suggested, will only be as good as the data it uses – and Syniti aims to provide the best quality data it can for Gen AI models to process.
XenData has added a Media Portal viewer to its on-prem and public cloud tape archive library so users can see previews of archived image and video files to select content for restoration.
The company builds the X-Series tape archive products, which have a front-end RAID disk cache. Previews, also called proxies, are low-resolution versions of the media file. They are created and written to disk when a media file is initially archived. XenData also supplies fully disk-based E-Series archive products. These scale out from one to four nodes, each with 280 TB of usable capacity. The Media Portal provides fast access to previews of archived files on tape that are otherwise slow to access and view.
XenData CEO Phil Storey said: “The Media Portal provides an excellent way for a user to know what content they have in their media archive. It is not a Media Asset Management system, but it provides a simple interface that provides the functionality that many of our users want.”
The Media Portal for Cloud runs on a physical or virtual Windows machine with a gateway to one or multiple public clouds, including AWS S3, Azure Blob Storage, and Wasabi object storage. It displays previews of all video and image files written via the gateway, including files stored on offline storage tiers such as AWS Glacier and the Azure Archive Tier.
The X-Series archive products can store offline cartridges externally as well as internally in the library racks. The Media Portal provides previews of all such external video and image content, together with the cartridge barcode information, which informs the user which LTO cartridges should be imported back into the library to be able to access the required content.
The Media Portal is sold as a software subscription and pricing starts at $980 a year. It will be available from May 2024.
Quantum stock price has been below the $1 mark on Nasdaq for more than 30 days and, as such, it was sent a letter by Nasdaq requesting it regain compliance.
The data manager has been dealing with an accounting issue regarding component pricing in product bundles that has affected its ability to file SEC reports for its second and third quarters of fiscal 2024. This issue has caused it to request a reporting date extension from Nasdaq to avoid delisting for not issuing financial reports. Now it has fallen foul of a second Nasdaq rule that threatens its listing status as well.
Quantum stock price history from Google Finance
The $1 stock price non-compliance letter arrived on March 19 and Quantum has asked for a hearing to present its plans to regain compliance plus a 180-day extension in which to do so.
CEO Jamie Lerner was appointed by Quantum in June 2018 following an October 2016 NYSE delisting threat for its stock price dipping below the $1 mark for 30 days. That delisting was avoided in April 2017 by a reverse stock split. Seven and a half years later, and following a June 2020 move to the Nasdaq stock market, it now faces a second delisting threat.
We may see a second reverse stock split to drive up the share price and regain Nasdaq listing compliance.
Separately, Quantum filed an SEC 8-K report detailing changes to its term loan credit and security agreement. This states that any financial proceeds from asset sales, aka “disposition of assets,” be prioritized to pay down existing debt. Quantum says this is consistent with its “broader efforts to prioritize certain financial and business projects targeting improvements to working capital, acceleration of new products and a more focused business.”
The recent i7 Raptor tape library product plan announcement is part of the “new products” aspect of this.
StoneFly has over 10,000 customers, but you’ve probably never heard of it. It supplies a unified SAN, NAS and object storage system has a three-layer virtual air gap system.
The biz supplies storage hardware and software presenting as an iSCSI SAN, Fibre Channel SAN, scale-out NAS and S3 object system, or all three with its StoneFly Fusion OS. This also powers hyper-converged infrastructure (HCI), backup and disaster recovery appliances which have the virtual air-gapping as a standard feature. Its Air-Gapped Vault runs in both on-premises deployments and also public cloud installations.
Mo Tahmasebi
CEO Mo Tahmasebi told us: “None of our customers have suffered from ransomware-corrupted data.”
StoneFly has an interesting and eventful past. It employs 125 people – 75 employees with contractors making up the rest. There are 25 salespeople, with Tahmasebi informing an IT Press Tour audience at its Hayward, CA, office: “I can close deals in 45 minutes.”
He said StoneFly has more than 10,000 customers, over 50,000 deployments and in excess of 2.5EB of storage capacity deployed. The customers include consumers, small-to-medium businesses, government agencies, universities, hospitals, financial institutions and Fortune 500 businesses. StoneFly products have been deployed in US Navy Littoral Combat Ships (LCS) and Virginia Class Nuclear Submarines.
Tahmasebi said: “We run our own datacenters, in Fremont, Oregon, and Massachusetts, using caged areas in co-los.” He also claims StoneFly has “high, very high” revenue and is “very profitable.” It spends virtually no money on marketing and gains customers by referral and word of mouth.
According to Tahmasebi, StoneFly kit is a third of the price of competitors like Dell and HPE, and lower cost than iXsystems. Its object backup target can be used with Veeam and costs less than an ObjectFirst Ootbi appliance.
Stonefly sells to Samsung and Toshiba in Korea and has undisclosed OEM partners.
Air-gapping
The air-gapping layers are at the repository, controller, and node levels.
Air-gapped repositories consist of one virtual storage controller connected to two target storage repositories. One target repository is network-facing, always accessible and available to user-groups, applications, etc. The second target repository is air-gapped, detached, and isolated.
Air-gapped repository diagram
StoneFly says air-gapped repositories can be deployed on popular hypervisors and public clouds. Policies can be defined to automatically turn-on (attach/connect) and turn-off (detach/disconnect) air-gapped repositories.
Air-gapped controller diagram.
The node-level air-gapping involves the chassis power being turned off so the node becomes invisible from the network point of view. The virtual air-gap then becomes a physical air-gap.
Stonefly history
Present day StoneFly came into being through an acquisition after the original company – founded as StoneFly Networks an iSCI storage supplier in San Diego in 2000, and owning the www.iscsi.com website – ran into not-making-enough-sales trouble in 2003. It was VC-funded with Allen Yuhas as its CEO from 2002 onwards by which time it had raised $12 million in funding. StoneFly competed with LeftHand Networks (bought by HP in 2008), EqualLogic (bought by Dell) and Intransa (crashed in 2013) in the IP SAN market.
Dynamic Network Factory (DNF) bought StoneFly Networks’ assets in 2006, paying $205,000 for them, changing the name to StoneFly and operating it initially as a San Diego-based DNF subsidiary. By then StoneFly had taken in a total of $34 million in funding developing its IP SAN products and had sold around 175 systems over a 13-month period.
That year, 2006, SAN interconnect hardware supplier QLogic became an OEM for Stonefly, as did Permabit. StoneFly integrated Permabit’s Albireo deduplication technology into the StoneFusion Network Storage Platform software, and Permabit was bought by Red Hat in 2017. QLogic was bought by Cavium in 2016, and Cavium was bought by Marvell in 2018.
DNF was founded by President and CEO Mo (Mohammed) Tahmasebi and CFO Macy Tafreshian in 1989. It started as a US subsidiary of Japanese conglomerate CSK Electronics, and focussed on storage software and hardware from 1998 onwards. DNF was spun off into a privately held entity in 1990, with Tahmasebi and Tafreshian self-funding it.
DNF has thousands of customers and major partners include Microsoft, Intel, Western Digital, Seagate, and Red Hat. The customer list includes include UC Berkeley, MIT, John Hopkins, the Department of Defense, the Federal Aviation Administration, Lockheed Martin, Bank of America, Citibank, Wells Fargo, Fujitsu, Nordstrom’s, Toshiba, PG&E, Safeway Corporation, Looksmart, CNET, and LSI.
Prior to starting DNF, Tahmasebi:
Worked at Sun Microsystems as an EnterpriseEngineering manager from 1982 to 1990;
Co-founded Pars which ran from 1990-1998 before being acquired;
Started up Tzone Corp & Research in 1997 and it was acquired in 2000;
Founded Computer Training Academy in 1997 which was acquired in 2000;
Set up Salesforce1 in 1997 – it was acquired in 2014;
Founded Trundl in 2014 for it to be acquired in 2019.
StoneFly CFO Macy Tafreshian worked with Tahmasebi as a VP at Pars, and was a co-founder at Salesforce1.com and DNF.
Snowflake finds GenAI analysis of data in its cloud data warehouses is rising and wants to encourage it.
The company has published a Snowflake Data Trends 2024 Report in which it looks at AI-related change in more than 9,000 users’ activities over the past 6-12 months.
Jennifer Belissent, principal data strategist at Snowflake, said: ”Conversational apps are on the rise, because that’s the way humans are programmed to interact. And now it is even easier to interact conversationally with an application. We expect to see this trend continue as it becomes easier to build and deploy conversational LLM applications, particularly knowing that the underlying data remains well governed and protected.”
The report says: “Organizations are picking their models, creating more complex LLM applications, making AI more available to a wider range of users, and reaping the benefits of a unified data platform. There has been a lot of hype around the transformational potential of AI, but judging from what we’re seeing in the Data Cloud, the frenzied fanfare is beginning to materialize into concrete results.”
Four trends are identified in the report, the first being greater use of machine learning (ML) functions, which grew 67 percent between July 2023 and January 2024. This “indicates the enthusiasm for, and the utility of, these ‘democratizing’ functions.”
But Snowflake admits via the report: “These are early days, and of course that growth surge starts from a relatively small initial point, but we’re excited to see sustained and growing interest in tools that put more and more of the power of advanced AI into the hands of less-technical users.”
LLM-powered apps being developed by Streamlit developers are on the rise, the report says. Streamlit is an open source Python language library that can be used in Snowflake to process data in Snowflake’s data warehouse. “Within the Streamlit developer community, between April 27, 2023, and Jan. 31, 2024, we saw 20,076 unique developers work on 33,143 LLM-powered apps (this includes apps that are still in development).”
Not all the developers are corporate ones, but most are: “In a survey of 1,479 respondents, nearly 65 percent said their LLM projects were for work.”
Python language use in the Snowflake Snowpark (non-SQL code development) environment is rocketing. It ”grew considerably faster than both Java and Scala in the last fiscal year: Python grew by 571 percent, while Scala grew by 387 percent and Java grew 131 percent.” Snowflake says Python is an AI-friendly language.
The third trend is the rise of GenAI chatbots compared to single-text-input LLMs, which Snowflake says don’t allow “refinement through iterative text input.” The report notes that Streamlit chatbot development is catching up to single-text-input LLMs, although the latter still dominates in terms of weekly use:
Snowflake’s fourth trend is increased use of its native apps. These are deployed inside Snowflake’s data cloud and the native app framework was previewed at the end of June last year. Comparing July 2023 to January 2024, Snowflake says it saw “311 percent growth in the number of Snowflake Native Apps published … 147 percent growth in installation/adoption of these applications … and usage of these apps grew 96 percent.”
The report adds that “given the choice, users want to build applications within their data platform – where the data is – rather than export copies of the data to external technologies.”
Users also want to manage access to their data in Snowflake with data governance functions restricting access to authorized users, the report states. “The use of all data governance functions has increased by 70 to 100 percent. As a result, the number of queries of protected objects has increased by 142 percent.”
Get a copy of the report here (registration required).
