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.
Sigma Computing Puts Business Teams in the Analytics Driver’s Seat with New “Sigma Workbooks”
Sigma Computing, the cloud analytics and business intelligence innovator, has combined the ease of spreadsheets with charts and data narratives in a single collaborative canvas purpose-built for business teams with the launch of Sigma Workbooks. Sigma Workbooks accelerates data-driven decisions by putting the power of analytics across billions of rows of live data directly into the hands of marketers, analysts, product managers, and other cross-functional business team members. The easy-to-use collaborative canvas enables everyone to find answers to critical questions in seconds, iterate and interact on analyses, share narratives in one unified place, and make data-driven decisions.
“Sigma has solved the data access versus control conundrum that IT and data teams have been grappling with for years,” said Sigma Computing Co-founder and CTO Rob Woollen. “With a data exploration and analytics interface that is similar to a spreadsheet, Sigma Workbooks meets knowledge workers, like operations, finance, and marketing teams, where they are when it comes to analytical skills and empowers them to find the answers they need to make decisions quickly. Sigma Workbooks also gives some much needed time back to data and BI teams so they can focus on larger initiatives, curating data sets, and supporting the data needs of business teams behind the scenes.”
SensoRy AI Seeks to Protect the Environment Using Artificial Intelligence
SensoRy AI announced its grand opening and revolutionary concept for utilizing artificial intelligence (AI) to prevent and predict hazards that threaten natural resources. The technology that SensoRy AI is developing uses a sensor network enabling prediction, early detection and growth projection of environmental hazards.
SensoRy AI is a startup focused on building a wireless mesh network of sensors that rely on machine learning (ML) to predict hazards prior to happening or project their growth after they happen. Unlike alternative cloud-based systems, SensoRy AI’s ML is placed on the edge of the network enabling real-time predictions and warnings.
The initial vision for SensoRy AI was developed by Ryan Honary after he witnessed the devastation caused by the Camp Fire in 2018. Ryan saw a need to create a solution that enables early detection and growth prediction to prevent significant escalations. What began as Ryan’s science project and prototype went on to win numerous awards, including a Naval Science Award from the Office of Naval Research (ONR), and a recommendation to apply for a Small Business Innovation Research (SBIR) grant.
Latest Release of the SnapLogic Fast Data Loader Provides Fast, Free Cloud Data Warehouse Loading for Everyone
SnapLogic announced the latest release of the SnapLogic Fast Data Loader, making it fast and easy for an IT specialist, data engineer, or business analyst to load data into a cloud data warehouse. With the SnapLogic Fast Data Loader, users can quickly and easily load data from SaaS applications such as Salesforce, ServiceNow, and Coupa, as well as cloud databases including Oracle and Microsoft SQL Server into a cloud data warehouse such as Amazon Redshift, Snowflake, or SAP Data Warehouse Cloud. With no coding required, fast parallel loading, full or incremental updating, and historical tracking, the SnapLogic Fast Data Loader helps users get fast, reliable data access to power their customer, product, and sales analytics initiatives.
“Cloud data warehouses are crucial to building a robust and modern analytics stack, however data loading from multiple sources can be slow and challenging and is holding enterprises back,” said Craig Stewart, CTO at SnapLogic. “The latest release of the SnapLogic Fast Data Loader helps users overcome these challenges so they can more quickly access the data to develop the analytics and insights they need to better engage customers, kick-start new product initiatives, and improve sales efficiency.”
AWS Announces General Availability of Amazon ECS Anywhere
Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ:AMZN), announced the general availability of Amazon Elastic Container Service (ECS) Anywhere, a new capability for Amazon ECS that enables customers to run and manage container-based applications on-premises using the same APIs, cluster management, workload scheduling, monitoring, and deployment pipelines they use with Amazon ECS in AWS. Amazon ECS Anywhere provides a fully managed container orchestration service that allows customers to easily run, scale, and secure Docker container applications on any customer-managed infrastructure in addition to all AWS Regions, AWS Local Zones, edge locations near end users for ultra-low latency (e.g. factory floors and mobile gaming), and hybrid infrastructure deployments (e.g. AWS Outposts and AWS Wavelength). There are no upfront fees or commitments to use Amazon ECS Anywhere, and customers pay only for the container instances they run.
“Customers have told us that while they need to run containers on their own infrastructure, they don’t want the hassle of operating their own cluster management software. They love the simplicity of Amazon ECS, the fact that it just works, and want the same reliability, scalability, and security of Amazon ECS wherever they run their applications,” said Deepak Singh, VP, Compute Services, AWS. “With Amazon ECS Anywhere we are proud to provide our customers exactly what they’ve asked for—a single service and control plane to manage their container deployments across AWS Regions, AWS Outposts, AWS Wavelength, AWS Local Zones, and customer-owned infrastructure, both in their data centers and at edge locations. Nothing else in the industry does that.”
NVIDIA Base Command Platform Provides Enterprises with Fast Path from AI Prototype to Production
NVIDIA unveiled NVIDIA® Base Command™ Platform, a cloud-hosted development hub that lets enterprises quickly move their AI projects from prototypes to production. The software is designed for large-scale, multi-user and multi-team AI development workflows hosted either on premises or in the cloud. It enables numerous researchers and data scientists to simultaneously work on accelerated computing resources, helping enterprises maximize the productivity of both their expert developers and their valuable AI infrastructure.
“World-class AI development requires powerful computing infrastructure, and making these resources accessible and attainable is essential to bringing AI to every company and their customers,” said Manuvir Das, head of Enterprise Computing at NVIDIA. “Deployed as a cloud-hosted solution with NVIDIA-accelerated computing, NVIDIA Base Command Platform reduces the complexity of managing NVIDIA Base Command Platform Provides Enterprises with Fast Path from AI Prototype to Production AI workflows, so that data scientists and researchers can spend more time developing their AI projects and less time managing their machines.”
Tellius Enhances AI-Driven Decision Intelligence Platform with Proactive and Personalized Insights
Tellius, the AI-driven decision intelligence platform, announced a series of major feature improvements designed to help businesses accelerate their analytics journey beyond dashboards to make better data-driven decisions. New Quick Start capability, proactive intelligence capabilities, and resource and data controls enable users to start analysis quickly, ask deep questions easily, and scale in a cost effective and secure manner. Many businesses struggle to unlock value from their data and analytics initiatives because of the overwhelming possibilities of analysis and surging data volumes. Tellius’s new Quick Start capability helps organizations—particularly those with limited data science resources—gain immediate, personalized insights from their data leading to a better understanding of the types of answers the data can provide. Quick Start asks users about metrics of interest, and then automatically generates tailored analytics content including data visualizations, inquiries, and AI-powered insights. From there, users can easily edit and build upon Quick Start content, making it faster and easier than ever for organizations to inform strategic business decisions.
“Our platform uniquely weaves in a robust intelligence layer that is missing in most of today’s business intelligence and data science tools,” said Ajay Khanna, CEO and founder, Tellius. “Personalized, proactive insights are the future of business intelligence and data science and this news is yet another step Tellius is taking to augment and tailor the enterprise analytics experience to go beyond dashboards. With maximum flexibility across clouds and on-premise solutions, Tellius is helping customers make the most of their data resources in a cost-effective manner—no matter where and how that data is stored.”
Splice Machine Introduces New Edition of Livewire Operational AI Platform for Industrial Users
Splice Machine, a real-time machine learning and AI solutions provider, today announced the release of Livewire Pulsar, the latest edition of its Livewire open source Operational AI platform for industrial IoT use cases. By using an upgraded Kubernetes architecture, the updated Livewire platform reduces costs, adds new AI features for increased productivity, and delivers a simplified and updated user interface. The Pulsar edition reduces the cost of ownership by introducing on-demand elastic operations, allowing enterprises to expand or decrease data storage resources depending on need. The new edition enables Apache Spark to scale up or down as needed with new min/max parameters for executors in both online analytical processing (OLAP) database operations and notebooks for ML, and offers an on-premise air gapped solution for plants that lack internet connectivity.
“Industrial enterprises have struggled to fully optimize their investments in AI. Our new Livewire Pulsar release makes it easier for companies to implement operational AI capabilities and allow plant operators to quickly leverage anomaly detection and predictive applications to prevent outages and improve overall plant performance,” said Monte Zweben, co-founder and CEO, Splice Machine.
AtScale CloudStart Bridges Business Intelligence and Enterprise AI to Cloud Data Platforms
AtScale, a leading provider of semantic layer solutions for modern business intelligence and data science teams, announced the launch of AtScale CloudStart for building powerful analytics infrastructure on cloud data platforms. This offering enables organizations to rapidly integrate AtScale’s semantic layer solution on leading cloud data management platforms. CloudStart provides customers a way to start with a smaller semantic layer investment aligned with entry points for cloud data platforms with the ability to scale seamlessly with your analytics infrastructure.
“We have seen cloud-first customers looking at an AtScale semantic layer as the ‘central nervous system’ for their business intelligence and data science programs,” said Christopher Lynch, Executive Chairman and CEO of AtScale. “CloudStart simplifies AtScale implementation on leading cloud platforms and accelerates time-to-value.”
New Varada Feature Eliminates Complexity and Cost Challenges of Text Analytics by Delivering Text-optimized Performance Directly on the Data Lake for SQL Data Consumers
Varada, the data lake query acceleration innovator, announced a new capability of its flagship platform designed to support text analytics workloads and help data teams deliver faster time-to-insights on exabytes of string-based data. Varada’s solution for interactive text analytics—integrated with the popular open source search engine Apache Lucene—works directly on the customer’s data lake and serves SQL data consumers out-of-the-box. As a result, data teams can achieve maximum performance without moving data, duplicating or modeling it.
“Text analytics has been evolving from on-premises solutions to cloud-based solutions,” said Eran Vanounou, CEO at Varada. “These approaches were innovative when introduced, but they have become complex and expensive, especially given the wide range of analytics platforms and stacks. At Varada, we’re introducing the next era in text analytics with a solution that runs directly on top of the customer’s data lake and alongside other analytics workloads. For the first time, users can deploy a text analytics solution without having to move data to expensive systems and complex, proprietary data schemas.”
Deeplite Announces Community Version of Neutrino for Optimizing Deep Learning Applications at the Network Edge
Deeplite, a provider of AI software designed to make other AI models faster, more compact and energy-efficient, announced its Deeplite Neutrino™ Community version. This free version provides a hands-on introduction while also enabling new connections and knowledge exchange among community members from different commercial, research and academic environments.
“The network edge is critical – it’s where users interact with devices and applications, businesses connect with customers, and the data to drive strategy and operations is generated. And while businesses want to push their AI software to the edge, the resource limitations of edge devices are holding them back,” said Nick Romano, CEO and co-founder at Deeplite. “Rather than spending time and money to try building optimization software on their own, our free Neutrino Community version lets deep learning engineers and researchers download our software to immediately test optimizing their models. This will accelerate more AI on the edge and move our mission of ‘AI for Everyday Life’ forward.”
GridGain Control Center Now Available as a Cloud Service
GridGain® Systems, provider of enterprise-grade in-memory computing solutions powered by the Apache® Ignite® distributed database, announced that an enhanced version of GridGain Control Center is available as a cloud service on a subscription basis. GridGain Control Center SaaS is another step by GridGain to move more of its solutions to the cloud to support accelerated cloud migration by customers. While GridGain Nebula, released last year, is a fully managed service for Ignite and GridGain, Control Center SaaS is a cloud-native solution for operations teams that prefer to manage their production environments.
“As the migration of infrastructure to the cloud accelerates, we are seeing more customers deploy Apache Ignite and the GridGain platform across their cloud environments, increasingly taking advantage of GridGain Control Center and the GridGain Nebula managed service,” said Greg Stachnick, Director of Cloud Product Management, GridGain Systems. “As a result, we continue to invest in new GridGain offerings, such as Control Center SaaS, to better enable customers to achieve the speed and scale required by their most demanding applications.”
Altair Announces Latest Release of Simulation Solutions
Altair (Nasdaq: ALTR), a global technology company providing solutions in simulation, high-performance computing (HPC), and artificial intelligence (AI) announces the release of its latest simulation solutions, including comprehensive computational fluid dynamics (CFD) and expanded capabilities in electronic system design (ESD). Updates include all major CFD solutions under a single license, expanded end-to-end electronic system design capability, and seamless access to the cloud.
“Throughout our 35-year history, Altair has developed and acquired countless specialized technologies to solve even the most challenging CFD problems,” said James R. Scapa, founder and chief executive officer, Altair. “We are proud to have the industry’s most robust CFD offering whose breadth and depth is unparalleled and can efficiently and effectively address a broad range of multidisciplinary challenges.”
Starburst announces new product release including advanced lakehouse analytics capabilities
Starburst, the analytics anywhere company, announced the availability of the latest version of Starburst Enterprise. The new release provides Starburst customers with net new capabilities alongside more advanced connectivity, improved performance, and more robust security. Among the net new capabilities, Starburst’s Delta Lake Connector now includes support for Data Manipulation Language (DML) to empower data analysts, platform admins, and engineers with Delta Lake write capability. By allowing companies to read and write to Delta Lake, Starburst can help with your path to a Lakehouse architecture.
“Managing a data lake is often time-consuming and can become an operational nightmare. Updating existing data in the traditional lake is difficult to do correctly and nearly impossible to do efficiently. This makes it difficult for data scientists and analysts to harness the power of their data,” said Matt Fuller, VP, Product and co-founder of Starburst Data. “The added DML feature to our Delta Lake Connector simplifies data management and accelerates data team productivity on their path to a Lakehouse architecture.”
Onit Debuts InvoiceAI, Artificial Intelligence for Legal Invoice Review
Onit, Inc., a leading provider of enterprise workflow and artificial intelligence platforms and solutions, including enterprise legal management, contract lifecycle management and business process automation, announced that it has introduced InvoiceAI, an artificial intelligence offering for first-pass legal invoice review and analytics, to its customers. InvoiceAI is analyzing historical invoices to train its models, while continuously learning from invoices to identify potentially non-compliant charges against a company’s billing guidelines and spend management best practices. This provides an opportunity to guide and retrain outside counsel on the corporate customer’s billing expectations and to demonstrate immediate savings in outside spend to internal stakeholders.
“Traditional legal invoicing and invoice review fail to show a law firm’s value or reveal the compliance and savings sought by corporate legal departments. Even when COVID-19 severely restricted travel in 2020, InvoiceAI identified an average of six figures of savings in travel-related billed time and expenses submitted to customers. It transforms the entire invoice lifecycle, lowering friction and aligning law firms and corporations on expectations and performance,” said Eric M. Elfman, Onit CEO and co-founder. “Expect more AI innovation from us this year, with further enhancements and a general availability launch for InvoiceAI coming in Q3.”
Pepperdata Introduces Observability and Optimization for Spark On Kubernetes
Pepperdata, a leader in big data performance management, announced that the Pepperdata product portfolio now provides autonomous optimization and observability for Spark applications running on Kubernetes.
Pepperdata offers full-stack observability for Spark on Kubernetes, allowing developers to manually tune their applications, while autonomously optimizing resources at run time. The combination of manual and autonomous tuning is necessary to deliver the best price and performance for these applications. Pepperdata uses machine learning across clusters, containers, pods, nodes, users and workflows to give you a complete understanding of your environment.
“Kubernetes is becoming increasingly important for a unified IT infrastructure, both in the cloud and the data center. Spark is the number one big data application moving to the cloud, but Spark applications tend to be quite inefficient. Optimization is key to successful implementations,” said Ash Munshi, CEO, Pepperdata. “We saw this early on with our customers, which is why we invested in the development of Spark on Kubernetes, together with Red Hat, Palantir and Google.”
Data Visualization Company Makes Collaborating and Decision Making with Business Data Easy
Observable, the collaborative data visualization company, founded by data veteran Mike Bostock, creator of the popular data visualization library D3.js, and engineering leader Melody Meckfessel, former vice president at Google, today launched Observable Templates, packaged data visualization use-case templates that put collaborative data exploration and decision-making in reach for any business user.
“Visualization helps us see and understand information in new ways, fundamentally changing our understanding of the world. By expanding data exploration beyond dataviz experts, Observable enables business users to work with data and gain insights leading to improved business outcomes and decision-making,” said Meckfessel. “With any new technology it can be difficult at first to envision its applicability to daily life. With real-world examples of data visualization, Observable Templates facilitates how people think with data to make decisions — faster and collaboratively.”
ScyllaDB Announces Scylla Enterprise 2021 NoSQL Database
ScyllaDB unveiled Scylla Enterprise 2021, the latest major release of ScyllaDB’s premium NoSQL database, offering the most stable codebase for production workloads at scale. Scylla Enterprise builds on the proven features and capabilities of Scylla Open Source and provides greater reliability from additional vigorous testing, as well as a set of unique enterprise-only features. Additions to Scylla Enterprise 2021 since its last major release include enhancements to its Amazon DynamoDB compatibility, faster searches on index lookups and many other improvements to performance, disk space management and security.
Scylla Enterprise is increasingly recognized as the trusted NoSQL database for delivering high throughput, predictable low-latency performance and a lower total cost of ownership. API-compatible with Apache Cassandra and Amazon DynamoDB, Scylla Enterprise scales up to any number of cores, offers multi-petabyte capacity with nodes as large as 60TB and reduces administrative overhead through its self-tuning operations.
“This year we embarked on our Project Circe, a one-year effort to make advancements across several important aspects of Scylla,” said Dor Laor, CEO and co-founder, ScyllaDB. “Scylla Enterprise 2021 includes many improvements that make Scylla an even more monstrous database.”
Adapdix announces EdgeOps DataMesh, first product of next-generation adaptive AI software platform EdgeOps
Adapdix, an industry leader in adaptive enterprise software, announced EdgeOps DataMesh™, the first software-only product based upon its Adapdix EdgeOps™ platform, delivering mass data virtualization, analysis, and AI inference at the edge in milliseconds.
The EdgeOps platform offers a growing suite of software products that begins with DataMesh, enabling enterprises to leverage their data to generate operational performance improvements through intelligent analytics, real-time asset optimization, and adaptive machine control. With semiconductor and precision manufacturers facing increasing pressure due to the global chip shortage, companies are able to use EdgeOps products to optimize their existing machines and processes in order to maximize their yield, throughput, and quality.
As a next-generation AI/ML product with data virtualization and analysis, DataMesh overcomes the typical hurdles of real-time operational data management by stitching together disparate data streams and performing data ingestion, pre-processing, and edge inferencing in milliseconds. DataMesh integrates all critical data streams for real-time analysis, enabling split-second decision-making for critical operations and reduced downtime of high-value assets with market-leading ease and speed of implementation.
“While others like to talk about “real-time,” we actually deliver it,” said Adapdix CEO Anthony Hill. “Because our platform operates at the source on the equipment and at ultra-low latency, we can ingest, pre-process, and analyze data integrating advanced AI applications – all in cycle time. With the ongoing worldwide chip shortage, semiconductor companies are urgently looking for ways to yield more from their existing resources and Adapdix software helps them achieve exactly that,” said Hill. “Several of our customers are already seeing phenomenal performance increases in equipment uptime and quality improvements—they are blown away that they can get up and running in less than a day and begin to see ROI within weeks.”
WANdisco Deepens Product Integration with Databricks to Accelerate Time to Value for Cloud-Scale Analytics
WANdisco, the LiveData company, announced that its LiveData Migrator platform, which automates the migration and replication of Hadoop data from on-premises to the cloud, can now automate the migration of Apache Hive metadata directly into Databricks to help users save time, reduce costs, and more quickly enable new AI and machine learning capabilities. For the first time, enterprises that want to migrate on-premises Hadoop and Spark content from Hive to Databricks can do so at scale and with high efficiency, while mitigating the many risks associated with large-scale cloud migrations.
“This new feature brings together the power of Databricks and WANdisco LiveData Migrator,” said WANdisco CTO Paul Scott-Murphy. “Data and metadata are migrated automatically without any disruption or change to existing systems. Teams can implement their cloud modernization strategies without risk, immediately employing workloads and data that were locked up on-premises, now in the cloud using the lakehouse platform offered by Databricks.”
Logi Analytics Launches New Capabilities to Provide Self-Service For Every User
Logi Analytics, a leading provider of embedded analytics solutions for software teams, launched new capabilities within Logi Composer, the first out-of-the-box development experience for embedded analytics. Logi Composer 6 provides enhanced control over the user experience with a framework of event listeners, self-service capabilities with dashboard interactivity and enterprise-grade security at every layer.
“End users want an analytics experience within their existing applications where they can customize, manipulate and query data to gain insights and empower decision making,” said Charles Caldwell, Vice President, Product Management at Logi Analytics. “And too many self-service solutions don’t match the needs and skill-level of the user. With this release, Logi Composer provides software teams a low-code, secure solution that will exceed users’ personalization and self-service requirements and offer administrators granular control to tune the analytics experience for different personas and user sophistication.”
PlanetScale Announces Developer-First, Instantly-Provisioned and Infinitely-Scalable Database
for Companies of All Sizes
PlanetScale, the creators of Vitess, announced a new database-as-a-service that lets developers create a new database in seconds that will grow as they grow, for years, with no limitations on scalability. Currently in use by Figma and MessageBird, PlanetScale has until now provided a hosted version of Vitess, the peerlessly-powerful open source database that underlies YouTube, Slack, Square and AirBNB. The new offering moves well beyond these foundations with a developer-first database requiring no knowledge or selection of all of the usual cloud zones, cluster sizes, and other DB-centric minutiae that others require and that increase developer overhead.
“Legacy databases have been developed with an eye to solving hard problems, but not to creating good experiences for developers, or to scaling as they scale,” said Sam Lambert, chief product officer at PlanetScale. “In a sense, the database industry forgives itself for making its products hard to use, due to the difficulty of the problems they are solving. We feel that’s unforgivable. PlanetScale is the fastest database to set up and fastest to iterate — it’s a developer tool, but we’ve also got you when it comes to scaling.”
Introducing CockroachDB 21.1
Cockroach Labs announced the release of CockroachDB 21.1, a substantial leap forward for the industry-leading distributed SQL database. CockroachDB already has a reputation as the world’s most powerful global database, and with this latest release it’s now also the easiest. CockroachDB 21.1 makes it dead simple to tie data to specific locations anywhere in the world within a single database — ensuring regulatory compliance, reducing latency, and improving fault-tolerance. CockroachDB 21.1 enables any developer — no matter their expertise — to start small, scale fast, and go global effortlessly.
“Our mission has always been to make building truly breakthrough applications easy for any developer. Too many development teams start on a platform that’s merely ‘good enough,’ and are then either hamstrung when their business grows, or have to suffer the pain of a migration,” said Spencer Kimball, CEO and cofounder at Cockroach Labs. “Your aspirations should not be constrained by your infrastructure. With CockroachDB 21.1, anyone can build their application from the beginning on a database that can take them from one cloud region to a global footprint, from three people in a garage to a multi-million dollar business.”
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