In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.
NICE Launches ElevateAI, The Market Leading AI as a Service (AIaaS), to Make Every CX Application Smarter
NICE (Nasdaq: NICE) announced the launch of ElevateAI, a new AIaaS solution that brings the power of Enlighten AI, its purpose-built CX AI, to the developer community. NICE is expanding its AI and Analytics leadership beyond the software market with AI services, enabling creators access to unrivaled data to enrich every moment of every customer interaction. Now with ElevateAI, creators can quickly and easily tap into NICE’s award-winning AI with developer-friendly APIs, instant sign-up capabilities, and affordable consumption-based pricing.
“The data-driven, AI future is already here, with organizations heavily prioritizing their investments in this direction,” said Barry Cooper, President, CX Division, NICE. “As the leader in AI for customer experience, we are very pleased to announce the release of ElevateAI, enabling organizations to benefit from NICE’s leading Enlighten AI models within their own developed software.”
Acceldata Open Sources Data Platform and Data Observability Libraries
Acceldata, a leader in data observability, announced a new open source version of its data platform, which gives enterprise data teams the ability to innovate with up-to-date data observability solutions at a lower cost. Several large enterprises from Fintech, Telco and Data Providers contributed, verified and have adopted this platform already. The open source data platform delivers stable and community-validated versions of data observability libraries, and supports public, private and hybrid environments, in order to meet the changing requirements of today’s enterprise.
“The dream of an open source data platform has been a broken one, until now,” said Rohit Choudhary, founder and CEO of Acceldata. “The guardians of open source have a responsibility to be open, over protectionism, and we take that role seriously as we continue to participate in, support and advance the community. Earlier in our careers, we used open source data tools, and subsequently, our team successfully built the world’s most comprehensive data observability platform. Now we are open sourcing a data platform and six data observability tools and sharing them with the community to adopt and advance these innovations to their benefit.”
Label Studio Revs Up Audio Labeling Performance with Version 1.7 of Popular Open Source ML/AI Data Labeling Platform
Data science teams gain powerful new features for annotating audio files with the availability of Label Studio v1.7, the most popular open source data labeling platform to support all data types—video, image, text and hypertext, time-series and audio. The latest release also adds support for Terraform and improvements to Helm charts for Kubernetes to ease the deployment and management of Label Studio.
“This release puts Label Studio at the forefront of audio labeling platforms in terms of usability, functionality and extensibility,” said Chris Hoge, head of community at Heartex, creators of Label Studio. “We’re also acting on feedback from our user community in the latest survey and support forums to ease deployments and management of the application with new options like Terraform. And for the growing segment of users deploying Label Studio at enterprise scale, the addition of Terraform support and Helm charts will simplify deployment automation and make it even easier to integrate Label Studio as a central platform for data-centric ML/AI operations.”
MarkLogic 11 Unlocks Value of Complex Data with Powerful Multi-Model Data Platform
MarkLogic, a leader in complex data and metadata management and portfolio company of Vector Capital, today announced new features delivered in MarkLogic 11, the latest release of its flagship MarkLogic Server product, that further enhance MarkLogic as a unified data platform with analytics, simplified deployment, management, and auditing—including in the cloud. Data fuels innovation and growth, but organizations are challenged to create business value from a constant stream of new data arriving in real time and from multiple sources. The MarkLogic data platform enables customers to connect and effectively leverage data and metadata as a single data resource. Data coupled with everything known about it means faster insights that accelerate innovation. MarkLogic 11 adds features that enable organizations to analyze and integrate multi-model data in new ways, and to make that data more accessible to developers and endpoints. Support for the increasingly popular GraphQL specification, for example, lets organizations expose multi-model data to BI tooling, and enhanced OpenGIS and GeoSPARQL support makes it easier to query — and tap into new workloads for — geospatial data. MarkLogic 11 also improves the platform’s manageability, auditability, and observability.
“MarkLogic 11 is the best data platform for complex data and metadata management, delivering unmatched data agility that will enable customers to get more value from their data and, in turn, make better, more informed decisions,” said Jeff Casale, CEO of MarkLogic. “With the acquisition of Smartlogic last year, we’ve entered a new era for MarkLogic focused on removing complexity and being the single place for breaking down data and knowledge silos.”
Arcitecta Unveils Radical Approach for Petabyte-Scale Data Resilience with Metadata-Based Data Protection
Arcitecta, a creative and innovative data management software company, unveiled Mediaflux® Point in Time, a revolutionary new backup and recovery approach that redefines data resilience at scale. Powered by Arcitecta’s Mediaflux data fabric, Point in Time offers metadata-based data protection that secures data at scale, expedites data recovery, and eliminates the significant cost and business impact of lost data. It also provides a strong first line of defense against crypto locking with the ability to roll back ransomware attacks with its unprecedented recovery point objectives (RPO) and recovery time objectives (RTO).
“We are now in the Data Age, where data volumes quickly grow to billions and trillions of files. Terabytes of data are rapidly becoming petabytes to exabytes of data and beyond. Traditional methods of backing up data are unviable at those scales,” said Jason Lohrey, founder and CTO, Arcitecta. “Organizations need a new approach to backup and recovery designed for the scale and complexity of today’s data demands. With Mediaflux Point in Time, we are redefining petabyte-scale data resilience and enabling enterprise organizations to eliminate the cost and business impact of lost data.”
Apache Cassandra® Releases Major Update, Enabling Extensibility for a Cloud Native Future
The Apache Cassandra Project has released 4.1 of Apache® Cassandra™, the open source, highly performant, distributed NoSQL database, charting a path to a more cloud native future and enabling an expanded ecosystem. The new release is part of Cassandra’s annual release schedule, and makes the database both easier to use for end users and easier to onboard key development requests from the community. Apache Cassandra is an Apache Software Foundation project. Download Apache Cassandra 4.1 here: https://cassandra.apache.org/_/download.html
“With an incredibly stable core that was delivered in 4.0, the project is now building on that milestone toward a more cloud native future,” said Mick Semb Wever, Apache Cassandra PMC member. “The latest release emphasizes externalizing important key functions into a pluggable interface, allowing developers to extend Cassandra without altering the stable core code. Organizations using Cassandra can be more selective how each combination of features is deployed and can add a layer of flexibility to future use cases that may not exist today. This includes storage engine choice, security components, schema and user management. Users of Cassandra will see the decoupled innovation in the ecosystem in the future without the need for a major release of the project.”
SingleStore Announces Key Innovations for World’s Only Unified Database Built for Real Time
SingleStore, the cloud-native database built for speed and scale to power real-time applications, announced the general availability of its 8.0 release, which features even faster analytics, improved developer experience and greater ease of use. SingleStoreDB powers real-time data innovation for hundreds of customers including more than 100 Fortune 500, Forbes Global 2000 and Inc. 5000 brands across fintech, ad-tech, martech and cybertech segments. Companies like Siemens, Uber, Palo Alto Networks, SiriusXM and others use SingleStoreDB to fuel real-time customer experience analytics, supply chain monitoring, sales and inventory management and interactive dashboards.
“The need for real time is here, but it doesn’t just happen through sheer will,” said Raj Verma, CEO, SingleStore. “Real time has been baked into our foundational design from very early on, and the continued innovation with the latest announcement sets us apart as the world’s only unified database that allows you to transact and reason with data in real time in a multi-cloud hybrid distributed environment.”
ClearML Shortens Time to Value in Machine Learning With NVIDIA TAO Toolkit
ClearML announced that the ClearML unified, end-to-end MLOps platform will be integrated with the latest NVIDIA TAO Toolkit 4.0 release. The NVIDIA TAO Toolkit speeds up the process of creating AI models, enabling customers to combine pretrained models with their own data to create custom computer vision and conversational AI models. With the ClearML integration, practitioners get improved visibility into the training, experimentation, and evaluation processes built into the TAO Toolkit, and multiple teams within an organization can now re-use the same process.
“ClearML is working to significantly shorten the time it takes for customers to see value from their investment in ML projects and deliver them to the market,” said Moses Guttmann, CEO and co-founder of ClearML. “By integrating the NVIDIA TAO Toolkit into the ClearML platform, we are able to significantly reduce the barriers of entry by offering state-of-the-art models available for training on custom data. Moreover, ClearML adds a visibility layer that provides TAO users with the extra information they need.”
Opaque Systems, Pioneer in Confidential Computing, Unveils the First Multi-Party Confidential AI and Analytics Platform
Opaque Systems, the pioneers of secure multi-party analytics and AI for Confidential Computing, announced the latest advancements in Confidential AI and Analytics with the unveiling of its platform. The Opaque platform, built to unlock use cases in Confidential Computing, is created by the inventors of the popular MC2 open source project which was conceived in the RISELab at UC Berkeley. The Opaque Platform uniquely enables data scientists within and across organizations to securely share data and perform collaborative analytics directly on encrypted data protected by Trusted Execution Environments (TEEs). The platform further accelerates Confidential Computing use cases by enabling data scientists to leverage their existing SQL and Python skills to run analytics and machine learning while working with confidential data, overcoming the data analytics challenges inherent in TEEs due to their strict protection of how data is accessed and used.
“Traditional approaches for protecting data and managing data privacy leave data exposed and at risk when being processed by applications, analytics, and machine learning (ML) models,” said Rishabh Poddar, Co-founder & CEO, Opaque Systems. “The Opaque Confidential AI and Analytics Platform solves this challenge by enabling data scientists and analysts to perform scalable, secure analytics and machine learning directly on encrypted data within enclaves to unlock Confidential Computing use cases.”
Sigma Computing Announces Live Editing for Collaborative Analytics
Sigma Computing, the fast, intuitive-to-use alternative to traditional business intelligence (BI), launched Live Edit, an industry-first feature that allows users to build and analyze data together at the same time. Live Editing allows users to explore, build, and iterate together directly and in real-time with the freshest data available. Now, instead of having to wait on data teams to share limited, static data and deal with the constant back-and-forth to draft and finalize reports, collaborators can communicate, coordinate, and even storytell together at the same time. Sigma’s Live Editing feature enables decisions to be made by decision makers working directly in the data sets, whenever, wherever, and collaboratively with whomever.
“Collaboration is the cornerstone of the future of analytics—we’re building a tool for how people work—rather than forcing them to work around artificial limits,” said Mike Palmer, CEO of Sigma Computing. “Our Live Editing customers are seeing over 90% adoption rate by their users because our spreadsheet interface is accessible and intuitive for most business professionals. Live Editing adds incredible value by enabling those users to work simultaneously in a Sigma Workbook at the same time, backed with power of all the data in the data warehouse.”
Kensu launches first 360 data observability solution to monitor data in motion and at rest in real-time
Kensu, the Data Observability company, announced enhancements to the Kensu platform which delivers the first 360 data observability solution on the market. It allows data teams to monitor data at rest and in motion in real-time across their data environments to cut the resolution time of data issues in half and restore trust in data.
“There has been a lot of hype about data observability. With this release, we offer companies the true 360° view and control over their data they’ve been searching for”, said Eleanor Treharne-Jones, CEO of Kensu. “Rather than just focusing on data at rest, our AI-powered platform is the first in the market to monitor data at rest and in motion, in real-time. At a time when budgets are under pressure, this disruptive approach will save countless hours fixing broken data pipelines and ensure businesses maximize the value from their data and their data teams.”
YugabyteDB 2.17 and New YugabyteDB Managed Features Focus on the Needs of Business-Critical Applications
Yugabyte, a leading open source distributed SQL database company, announced a wave of new product innovations with the availability of YugabyteDB 2.17 and major enhancements to YugabyteDB Managed. The latest releases address the database needs of the most demanding, mission-critical applications, offering the data protection, global deployment and streamlined usability enterprises need to accelerate their modernization initiatives.
“Organizations looking to modernize new and existing core transactional applications need to move away from costly monolithic databases, but barriers to enterprise-readiness like data protection, security, and usability can block the way,” said Karthik Ranganathan, co-founder and CTO, Yugabyte. “YugabyteDB 2.17 removes key obstacles to database modernization. It empowers organizations with a host of new benefits unmatched in both legacy and many modern databases, putting developer productivity at the core.”
The Modern Data Company Launches DataOS®
The Modern Data Company announced DataOS®, the multi-cloud data operating system that makes data simple for enterprises to drive decisions. Created to quickly operationalize complex data infrastructures, DataOS is a modern, open and composable data management platform as a service (PaaS) that provides total data visibility and turns data into insights that drive actionable intelligence. DataOS is a first-of-a-kind data operating system that gives control of data back to enterprises that have traditionally been beholden to an array of point solutions through constant integrations. It breaks down data silos by laying on top of any existing data infrastructure to provide an interoperability layer to operationalize data to drive trusted decisions.
“DataOS makes your existing legacy infrastructure work like a modern data stack without rip-and-replacing anything,” said Srujan Akula, CEO and co-founder of The Modern Data Company. “It costs significantly less, gives you complete control of your data, and makes creating new data-driven applications and services simple for developers and business users alike.”
Aiven Introduces an Open Source Streaming Ecosystem for Apache Kafka
Aiven, the open source cloud data platform, announced a complete open source streaming ecosystem for Apache Kafka®, delivering a robust– and fully open source real-time data ecosystem with the latest additions of its beta service of Aiven for Apache Flink®, a stream processing framework, and Klaw, a data governance tool for Apache Kafka.
“As a leader in the open source community, Aiven is on a mission to manage software that makes developers’ lives easier – and with our complete, open source streaming ecosystem of technologies around Aiven for Apache Kafka, we’re able to do just that and more for our users,” said Oskari Saarenmaa, CEO and Co-Founder of Aiven. “I couldn’t be more excited to share this streaming ecosystem with the community and continue fueling innovative, data-intensive open source technologies.”
Zyte’s Innovative API is a Step-Change in Web Data Collection
Zyte®, a leader in web data extraction for businesses and enterprises, announced its newest web data extraction solution, Zyte API – a self-service API that consolidates virtually every known web scraping technology and technique into a deceptively simple, but powerful API for collecting web data at virtually any scale. Using the new Zyte API, organizations will have the tools necessary to extract data from even the most sophisticated sites using state-of-the-art techniques in an automated “all-in-one” solution, freeing teams from time-consuming configuration and anti-scraping workarounds.
“The collection of web data is used every day to solve real-world problems, including providing insights on everything from business challenges, economic indicators, the spread of diseases, and even combatting human trafficking,” said Shane Evans, CEO of Zyte. “We are unequivocal believers in the immense value that Internet data has for creating value, enriching society, and unlocking social and economic benefit. Zyte is committed to providing powerful tools that empower people and organizations, both large and small, to collect this valuable, publicly available data to unlock new solutions, build intelligence, and create new opportunities in the easiest, most reliable, cost-effective way possible.”
ClickHouse Launches Cloud Offering For Fast OLAP Database Management System
ClickHouse, Inc, creators of the online analytical processing (OLAP) database management system, announced the general availability of their newest offering, ClickHouse Cloud, a lightning-fast cloud-based database that simplifies and accelerates insights and analytics for modern digital enterprises. With no infrastructure to manage, ClickHouse Cloud architecture decouples storage and compute and scales automatically to accommodate modern workloads, so users do not have to size and tune their clusters to achieve blazing-fast query speeds. This launch includes a host of new product features, enhancing the security, reliability and usability of ClickHouse Cloud.
“The advantage of ClickHouse is speed and simplicity, and ClickHouse Cloud takes that to a new level, enabling businesses to start a service and analyze data a fraction of the cost of other solutions on the market,” said Aaron Katz, CEO of ClickHouse. “In just a few months, the ClickHouse Cloud beta has gained over 100 customers and thousands of new users spanning across developers, data analysts, marketing and other critical areas of business where data is analyzed and stored.”
CockroachDB Introduces Functions to Increase Development Efficiency and Unlock Easier Migrations to the Cloud
Cockroach Labs, the company behind a leading cloud-native distributed SQL database CockroachDB, announced CockroachDB 22.2, which delivers new functionality aimed at increasing developer and operator efficiency while simplifying the architecture of data-intensive applications and enabling teams to migrate off legacy technology to the cloud.
“By partnering closely with our customers as they build scalable, resilient, and low-latency applications, we’ve put together a release that is a leap forward in CockroachDB’s capabilities,” said Nate Stewart, Chief Product Officer at Cockroach Labs. “CockroachDB 22.2 streamlines application development, helps developers quickly troubleshoot performance issues at any scale, and significantly brings down the cost of powering event-driven architectures.”
Variscite Simplifies AI/ML and Multimedia at the Edge with Python API for System on Modules
Variscite, a leading worldwide designer and manufacturer of System on Modules (SoMs), announced the official launch of the Variscite Python API developer center. The Variscite Python API, also known as pyvar, simplifies the development of machine learning and multimedia applications for devices built on Variscite’s i.MX8-based SoMs. With the API, building and programming embedded systems and smart/edge devices for AI/ML is faster and easier, even for beginners.
Variscite Python API eases the development process of embedded systems using cameras, sensors, displays, and user interfaces. It also provides an easy way to run and communicate with Cortex-M applications from the Cortex-A side, for fast processing at low power. The API’s developer center provides ‘how to’ guides, documentation and quick source code examples.
“Capture, recognition, and processing of image, audio, and video data are increasingly used in embedded edge devices for any kind of environment, from transportation to healthcare, robotics, and agriculture,“ said Ofer Austerlitz, VP Business Development and Sales of Variscite. “Our customers require additional AI/ML capabilities at the edge to run complex and advanced applications, and the Variscite python API enables faster and easier deployment with our i.MX8 SoMs.”
Zilliz Unveils Zilliz Cloud, the New Industry Standard for Vector Database as a Service
Zilliz, provider of the leading vector database built on Milvus for enterprise-ready AI, announced that Zilliz Cloud is generally available and ready for enterprise production workloads with a 99.9 percent guaranteed uptime service level agreement (SLA). Featuring the Zilliz team’s expertise in running some of the largest-scale and most complicated vector similarity search in production, the fully-managed service makes it easy for companies to deploy and run their image retrieval, video analysis, recommendation engines, targeted ads, customized search, smart chatbots, fraud detection, network security, new drug discovery, and many other AI applications at scale.
“We started Zilliz with building an open-source solution Milvus to bring the capability of vector database to the masses. Now with Zilliz Cloud, we’re thrilled to offer the experience valued by our open-source users in an even more simplified manner with a fully-managed cloud service. It takes only a few clicks to start up your own instance on Zilliz Cloud, and less than a day to build a highly optimized vector similarity search service to extract valuable insights. We believe that the combination of extraordinary performance and peerless scalability delivers significant benefits to our customers,” says Charles Xie, founder and CEO of Zilliz.
Mode Raises the Bar on The Future of Modern Business Intelligence
Mode Analytics, the modern Business Intelligence (BI) platform that brings data teams and business teams together to drive impact, introduced Datasets: curated, reusable building blocks that power self-service reporting and code-free data exploration. Mode also unveiled a completely new look and feel, an important element of its enhanced user experience as the first BI platform built around the way modern data teams work.
“Modern BI shouldn’t force you to choose between the needs of data teams and business teams,” said Gaurav Rewari, CEO, Mode Analytics. “We believe that by bringing everyone together for ‘multimodal’ data analysis, organizations can move faster, make better decisions, and increase the impact of their modern data stack.”
Spiro.AI Incorporates New AI-Generated Content into Sales Platform to Accelerate Manufacturing Agility
Spiro.AI announced it has added more AI-generated content into its customer platform, with even more planned for next year. This AI content generator, coupled with the ability of Spiro’s AI Engine to automatically collect customer data and then proactively alert next best actions, now provides manufacturers and distributors with an even more dynamic platform that enables external-facing teams to work in more efficient, meaningful ways.
The Spiro AI Engine automatically collects data from all customer communications, and then provides an AI-generated transcription of calls for each customer and individual contact. With this new release, Spiro’s AI Engine now generates a call summary in order to provide fast, concise, relevant updates. The AI Engine also now drafts an email based on the call, which an account manager can quickly send to their customer to recap their conversation and capture next steps. For this release, Spiro is leveraging OpenAI’s GTP-3’s advanced AI features.
“With AI and machine learning, the more data, the better,” said Spiro.AI CEO Adam Honig. “Spiro has spent eight years collecting mountains of data about virtually every customer interaction, and has focused on synthesizing that data to make it instantly accessible to everyone. OpenAI has provided an incredible tool to help us take advantage of this wealth of data in ways that help customer-facing employees take the actions needed to build stronger relationships with their prospects and customers.”
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