e6data to degree the enjoying area for purchasers by negating the immense pricing energy a handful of distributors take pleasure in as a consequence of varied new types of compute ecosystem lock-in at totally different layers of the info stack.
In right this moment’s digital-first panorama, enterprises depend on highly effective information and AI capabilities to gas innovation, improve buyer experiences, and optimize operations. Nevertheless, they’re set to spend a staggering $100b in 2024 on information intelligence platforms to derive worth from their very own information. Laser targeted on this information compute spend problem, e6data is right this moment asserting a $10m funding spherical because it goals to half the invoice of companies in search of to investigate their very own information. The sequence A funding spherical was led by Accel Companions with participation from Beenext and others.
Knowledge intelligence platforms enable enterprises to get insights from their very own information to make enterprise choices and serve workloads together with information engineering, analytics, machine studying, and now generative AI. With the rising quantity of knowledge and the necessity to extract most worth from it, enterprises shall be taking a look at a large invoice to make the most of this information. The whole addressable market (TAM) for information and AI options is slated to the touch $230 billion in 2025, with 60% of CXOs planning to extend their spending over the subsequent yr.
Vishnu Vasanth, co-founder and CEO commented: “This fast improve has made information intelligence platforms the second largest IT spending class – behind solely cloud spend for operational methods and utility infrastructure. It’s fueling the meteoric rise of knowledge warehouse and information lakehouse firms comparable to Snowflake and Databricks, and the fast progress of corresponding choices from AWS, Azure, and Google Cloud.”
Nevertheless, because the spending grows, ROI issues are reaching a boiling level. Enterprise expertise leaders want a strategy to concurrently improve efficiency and entry new capabilities, whereas concurrently controlling prices. They more and more discover there are not any compelling alternate options to the established order and are cautious of rising types of ecosystem lock-in. “Reputable ROI issues stand in the way in which of enterprises realizing the complete potential of knowledge & AI. Furthermore, organizations can’t freely transfer lakehouse desk codecs, information catalogs, compute suppliers, and cloud suppliers with out opposed price-performance impacts, the necessity for information motion, and cumbersome utility migrations. We goal to deal with this by way of our work at e6data” added Vishnu Vasanth.
To handle these challenges, e6data has developed a brand new breed of “compute engine” for information intelligence platforms that helps enterprises amplify ROI on their present platforms and architectures and escape ecosystem lock-in; all with zero friction to adoption within the type of zero information motion, zero utility migration, and 0 down-time.
e6data plans to increase entry to its Lighthouse Buyer Program, which provides the e6data resolution as a managed service for the heaviest or most urgent use-cases of enterprise prospects, full with manufacturing assist {and professional} companies.
Knowledge intelligence platforms like information lakehouses and warehouses are the inspiration of all analytics and AI. At their core, they use distributed “compute engines,” whether or not open-source or vendor-backed, for each type of processing spanning ingestion, transformation, dashboards, stories, ML mannequin coaching and inference, in addition to RAG-based generative AI purposes.
Nevertheless, present compute engines are constructed on monolithic architectures with centralized parts for many points of a question or job’s life cycle. This creates challenges with respect to value, efficiency, concurrency dealing with, and uptime – significantly on compute-intensive heavy workloads that enterprises more and more encounter as they function at manufacturing scale.
e6data’s founding workforce noticed a possibility to deal with these gaps with a brand new engine structure and distributed processing mannequin that’s disaggregated, decentralized, and Kubernetes-native. The e6data engine outperforms main industrial and open-source options throughout real-world heavy workloads and in style benchmarks: 5x increased efficiency, whole value of possession (TCO) financial savings of greater than 50%, and a very format-neutral method that negates ecosystem lock-in.
With a multi-disciplinary mixture of distributed methods engineers, database builders, open supply committers, and go-to-market leaders from Microsoft, ThoughtWorks, IBM DB2, Cisco, SAP, and Thoughtworks, the e6data workforce’s prior experiences in over 100+ large-scale information intelligence platforms gave them a first-hand view of the altering expertise panorama, and the challenges going through enterprises as they scaled their information & AI wants.
e6data has already signed up publicly listed Fortune 500 enterprises in addition to excessive progress firms as prospects. It’s anticipating explosive progress as a consequence of rising demand for compute-intensive heavy workloads throughout high-volume information merchandise (e.g. customer-facing and enterprise dashboards, stories), superior analytics on close to real-time information (personalization, fraud/danger, stock planning), and production-grade generative AI purposes (e.g. RAG for search, suggestion, buyer assist).
Knowledge platform spend is already the highest 2 CXO spend. Nevertheless, the biggest and fastest-growing spend drivers are usually from strategically necessary, nondiscretionary workloads.
In keeping with Gartner, greater than 80% of enterprises shall be gen AI in manufacturing by 2026 which is able to additional gas the necessity for e6data’s high-efficiency, format-neutral compute infrastructure providing.
Rajaraman Santhanam, COO of Chargebee added: “We’ve been collaborating with e6data throughout a number of inside and external-facing analytics use instances, all constructed on Chargebee’s multi-purpose, scalable information lakehouse platform. We’re seeing thrilling alternatives to innovate for our prospects. We’ve efficiently supported concurrencies of over 1,000 QPS on close to real-time (NRT) information and complicated queries whereas sustaining shopper latencies of lower than 2 seconds. Different lakehouse engines we evaluated struggled to realize this degree of efficiency and scalability, regardless of being extra useful resource intensive.”
With its distinctive providing, e6data hopes to degree the enjoying area for purchasers by negating the immense pricing energy a handful of distributors take pleasure in as a consequence of varied new types of compute ecosystem lock-in at totally different layers of the info stack. Organizations can’t freely transfer lakehouse desk codecs, information catalogs, compute suppliers, and cloud suppliers with out opposed price-performance impacts, the necessity for information motion, and cumbersome utility migrations.
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