BIG DATA MANAGEMENT

Rockset Releases Rollups for Up To 100X More Cost-Effective Real-Time Analytics on Streaming Data

Rockset | August 26, 2021

Rockset, the real-time analytics company, today unveiled a major product release that makes real-time analytics on streaming data from sources like Apache Kafka, Amazon Kinesis, Amazon DynamoDB, and data lakes a lot more accessible and affordable for every enterprise. With this launch, customers can use standard SQL to perform real-time data transformations and pre-aggregations continuously as new data is ingested from any source — a game-changing new feature that represents an industry first in the analytics database landscape. This significantly reduces engineering effort on real-time data pipelines, while cutting both storage and compute costs for real-time analytics at cloud scale. As a result, any developer can build real-time, interactive dashboards and data-intensive applications on massive data streams in record time, at a fraction of the cost.

For today’s digital disruptors striving to harness the power of streaming data, the old way of preparing and loading data into a traditional database and manually tuning each query no longer works. The ability to onboard new streaming data sets quickly and easily using continuous SQL transformations and rollups means developers do not need to manage complex real-time data pipelines. Eliminating this complexity makes real-time analytics more accessible for anyone who speaks SQL. When combined with Rockset’s unique indexing approach, which delivers low latency analytics no matter the shape of the data or type of query, developers can iterate faster and innovate more on streaming data applications. Until now, analyzing high volume streaming data in real time has been prohibitively expensive in the industry, but with this release new data can be transformed and pre-aggregated as it arrives, so the cost of storing and querying that data is reduced by a factor of 10-100x.

Imagine you’re a payment processor, handling millions of payments between thousands of merchants and millions of customers. You would need to monitor all those transactions in real time and run advanced statistical models to detect anomalies and catch fraud. Storing raw events and constantly recalculating metrics would mean your storage footprint grows at an alarming rate and queries become prohibitively slow and expensive. Instead, with this release Rockset allows you to “rollup” data as it arrives, so your data is still queryable in real time, but at a fraction of the cost and with better performance.

Built by the team behind the online data infrastructure that powers Facebook Newsfeed and Search, Rockset is inspired by the same indexing systems that power real-time analytics at cloud scale. Rockset automatically indexes all fields in a Converged Index™, delivering fast SQL queries on fresh data, for cloud-native speed, scale, and flexibility in real-time analytics. This is revolutionary across a broad range of digital platforms and apps, including e-commerce, logistics and delivery tracking, gaming leaderboards, fraud detection systems, health and fitness trackers, and social media newsfeeds.

“Your modern cloud data stack is incomplete without a real-time database purpose-built for ingesting, transforming, and analyzing streaming data. Warehouses simply don’t cut it — they are built for batch analytics and become prohibitively slow and expensive for high volume streaming data,” said Venkat Venkataramani, CEO and co-founder at Rockset. “Transforming massive torrents of raw data streams to accurate high-quality aggregates is essential for achieving real-time analytics at cloud scale. With this release, Rockset makes building massively scalable real-time aggregations as simple as writing a simple SQL query, and a lot more budget-friendly.”

New features available now on Rockset’s cloud service include the ability to:
  • Continuously transform during ingestion: Customers can use SQL to transform streaming data as it is ingested, eliminating time and effort required to maintain complex real-time data pipelines.
  • Rollup data during ingestion: Customers can use SQL to pre-aggregate streaming data as it is ingested, reducing the cost of storing and querying data by 10-100x.
  • Set time-based partitioning and retention: Customers can set highly efficient data retention policies for time series and streaming data, enabling automatic deletion of aging data for reducing costs.

Rockset’s usage-based pricing has two components: cloud compute for real-time data processing and hot storage. To learn more, join our tech talk on the Modern Real-Time Data Stack: Emerging Cloud Architectures for Streaming Data Analytics.

About Rockset
Rockset is a real-time indexing database in the cloud, built by a team of industry veterans with decades of experience in web-scale data management and distributed systems at companies including Facebook, Yahoo, Google, Oracle and VMware. Rockset is backed by Greylock and Sequoia.

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BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Comet Introduces Kangas, An Open Source Smart Data Exploration, Analysis and Model Debugging Tool for Machine Learning

Comet | November 17, 2022

Comet, provider of the leading MLOps platform for machine learning (ML) teams from startup to enterprise, today announced a bold new product: Kangas. Open sourced to democratize large scale visual dataset exploration and analysis for the computer vision and machine learning community, Kangas helps users understand and debug their data in a new and highly intuitive way. With Kangas, visualizations are generated in real time; enabling ML practitioners to group, sort, filter, query and interpret their structured and unstructured data to derive meaningful information and accelerate model development. Data scientists often need to analyze large scale datasets both during the data preparation stage and model training, which can be overwhelming and time-consuming, especially when working on large scale datasets. Kangas makes it possible to intuitively explore, debug and analyze data in real time to quickly gain insights, leading to better, faster decisions. With Kangas, users are able to transform datasets of any scale into clear visualizations. “A key component of data-centric Machine Learning is being able to understand how your training data impacts model results and where your model predictions are wrong. “Kangas accomplishes both of these goals and dramatically improves the experience for ML practitioners.” Gideon Mendels, CEO and co-founder of Comet Putting Large Scale Machine Learning Dataset Analysis at Your Fingertips Developed with the unique needs of ML practitioners in mind, Kangas is a scalable, dynamic and interoperable tool that allows for the discovery of patterns buried deep within oceans of datasets. With Kangas, data scientists can query their large-scale datasets in a manner that is natural to their problem, allowing them to interact and engage with their data in novel ways. Noteworthy benefits of Kangas include: Unparalleled Scalability: Kangas was developed to handle large datasets with high performance. Purpose Built: Computer Vision/ML concepts like scoring, bounding boxes and more are supported out-of-the-box, and statistics/charts are generated automatically. Support for Different Forms of Media: Kangas is not limited to traditional text queries. It also supports images, videos and more. Interoperability: Kangas can run in a notebook, as a standalone local app or even deployed as a web app. It ingests data in a simple format that makes it easy to work with whatever tooling data scientists already use. Open Source: Kangas is 100% open source and is built by and for the ML community. Kangas was designed for the entire community, to be embraced by students, researchers and the enterprise. As individuals and teams work to further their ML initiatives, they will be able to leverage the full benefits of Kangas. Being open source, all are able to contribute and further enhance it as well. “Interoperability and flexibility are inherent in Comet’s value proposition, and Comet aims to expand on that value through open source contributions,” added Mendels. “Kangas is a continuation of all of our efforts, and we couldn’t wait to get its capabilities into the hands of as many data scientists, data engineers and ML engineers as possible. We believe by open sourcing it, Comet can help teams get the most out of their ML projects in ways that have not been possible previously.” Kangas is available as an open source package for any type of use case. It will be available under Apache License 2 and is open to contributions from community members. About Comet Comet provides an MLOps platform that data scientists and machine learning teams use to manage, optimize, and accelerate the development process across the entire ML lifecycle, from training runs to monitoring models in production. Comet’s platform is trusted by over 150 enterprise customers including Affirm, Cepsa, Etsy, Uber and Zappos. Individuals and academic teams use Comet’s platform to advance research in their fields of study. Founded in 2017, Comet is headquartered in New York, NY with a remote workforce in nine countries on four continents. Comet is free to individuals and academic teams. Startup, team, and enterprise licensing is also available.

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BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Precisely Works with AWS to Power Mainframe Modernization for Real-Time Access to Data

Precisely | December 01, 2022

Precisely, the global leader in data integrity, today announced it is working with Amazon Web Services (AWS) on its AWS Mainframe Modernization service. The integration offers real-time replication of mainframe data to AWS leveraging Precisely Connect, allowing customers to securely and efficiently migrate data, as well as access mainframe data on AWS for more powerful analytics. This new scope of work delivers a mainframe modernization solution to the market that allows customers to replicate mainframe data onto AWS with zero downtime. The functionality allows customers to build resilient, high-performance data pipelines that connect data from their mainframe databases to AWS services like Amazon Relational Database Service (Amazon RDS), Amazon Aurora, Amazon Simple Storage Service (Amazon S3), Amazon EMR, Amazon Managed Streaming for Apache Kafka (MSK), Amazon Redshift, Snowflake on AWS, and more. By accelerating access to mainframe data on AWS, businesses can get mainframe migration projects done on time and on budget, all while extending the value of mission-critical, and high investment, mainframe systems. The integration solution works within a business’s existing architecture, allowing teams to future-proof solutions and be flexible when introducing new applications and use cases. Customers that have already begun taking advantage of these joint capabilities include AAA Life Insurance: “Our customers rely on us to provide financial protection for their loved ones, and with over 1,500,000 active policies, central to success is real-time access to trusted data across multiple sources. This includes mainframe systems - which are notoriously challenging to integrate effectively,” said Steven Hinzmann, Manager of Application Development at AAA Life Insurance. “Precisely Connect allows us to quickly and easily access vast volumes of historical business and customer data, which is then replicated to the AWS environment where it can be leveraged for advanced analytics. The combination of Precisely’s rich heritage in handling mainframe data with AWS’s cloud platform has been unbeatable for allowing us to innovate and drive the best possible customer experience." “Data is the lifeblood of the digital economy and the pipelines that carry it are essential to a business’s IT infrastructure. “Together with AWS, we can help our customers to maximize their data and investments - unlocking the true potential of their critical data assets to power their business by making critical data assets available for AWS and for advanced analytics.” Eric Yau, Chief Operating Officer at Precisely “AWS and Precisely empower our customers to build trust in their data,” said Bill Platt, General Manager for Migration Services at AWS. “By integrating data from complex mainframe systems directly onto AWS, customers can rely on their data to be the driving force of confident analytics, and ensure they are deriving maximum value from their infrastructure investments.” About Precisely Precisely is the global leader in data integrity, providing accuracy, consistency, and context in data for 12,000 customers in more than 100 countries, including 99 of the Fortune 100. Precisely’s data integration, data quality, data governance, location intelligence, and data enrichment products power better business decisions to create better outcomes.

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BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT, BUSINESS STRATEGY

Datamatics positioned as the Challenger in the 2022 SPARK Matrix for Data Management & Analytics Services by Quadrant Knowledge Solutions

Datamatics | November 11, 2022

Quadrant Knowledge Solutions announced today that it has named Datamatics, a global Digital Technologies, Operations, and Experiences Company, as a 2022 technology Challenger in the SPARK Matrix analysis of the global Data Management & Analytics Services market The Quadrant Knowledge Solutions SPARK Matrix™ includes a detailed analysis of global market dynamics, major trends, vendor landscape, and competitive positioning. The study provides competitive analysis and ranking of the leading technology vendors in the form of its SPARK Matrix. It gives strategic information for users to evaluate different provider capabilities, competitive differentiation, and market position. According to Sreejith PS, Analyst, Quadrant Knowledge Solutions, "Datamatics provides enterprise data management consulting services by assessing their client's current strategy. This assists in either building on the client's available technology stack by utilizing Datamatics' IP, solution accelerators, and frameworks, or in form of offering bespoke BI Analytics services by utilizing its industry expertise & BI platforms. The company also provides a data management competence matrix comprising data governance, data architecture, data models, data quality, and data security as a part of its well-curated ecosystem of partners and products." Sreejith added, "Datamatics, with its comprehensive capabilities, compelling customer references, comprehensive roadmap and vision, has received strong ratings across the parameters of technology excellence and customer impact and has been positioned as a challenger in SPARK Matrix: Data Management & Analytics Services, 2022." Sachin Rane, Executive Vice President & Head – Software Solutions, Datamatics Global Solutions Limited, expressed, "Data management is one of the topmost priorities of the enterprises in today's time, there are silos of information or data across organization, and they are looking for a cohesive strategy to manage it. "Datamatics' Enterprise Data Management (EDM) practice offers end-to-end data management solutions as well as point solutions to enable businesses disembark on their data to intelligence journey. He further added, "We are pleased to be a part of the Quadrant Spark Matrix - Data Management and Analytics Services, 2022. This reflects the robust comprehensive functional service capability, domain-specific rich expertise and global service coverage of Datamatics EDM." About Datamatics Datamatics a Digital Operations, Technology and Experiences company that provides intelligent solutions for data-driven businesses to increase productivity and enhance the customer experience. With a completely digital approach, Datamatics portfolio spans Information Technology Services, Business Process Management, Engineering Services and Big Data & Analytics all powered by Artificial Intelligence. It has established products in Robotic Process Automation, Intelligent Document Processing, Business Intelligence and Automatic Fare Collection. Datamatics services global customers across Banking, Financial Services, Insurance, Healthcare, Manufacturing, International Organizations, and Media & Publishing. The Company has a presence across 4 continents with major delivery centers in the USA, India, and the Philippines. About Quadrant Knowledge Solutions Quadrant Knowledge Solutions is a global advisory and consulting firm focused on helping clients in achieving business transformation goals with Strategic Business and Growth advisory services. At Quadrant Knowledge Solutions, our vision is to become an integral part of our client's business as a strategic knowledge partner. Our research and consulting deliverables are designed to provide comprehensive information and strategic insights for helping clients formulate growth strategies to survive and thrive in ever-changing business environments.

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BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Veritonic Added to List of Acast’s Preferred Audio Attribution Partners

Veritonic | December 09, 2022

Veritonic, the industry’s comprehensive audio analytics and research platform, announced today that they have been approved as an attribution partner by Acast, the world’s largest independent podcast company. As a result, the more than 2,400 advertisers and 88,000 podcasters that use the Acast platform to distribute their podcast content can elect to utilize Veritonic’s robust attribution capabilities to optimize and further increase the ROI of their audio campaigns. “We are pleased to partner with Acast to support brands, agencies, and publishers with the holistic data and analytics they need to increase their reach and ROI with audio. "The powerful combination of our attribution and brand lift technology provides unparalleled and comprehensive measurement of audio campaigns from top to bottom in one unified and intuitive platform.” Scott Simonelli, chief executive officer of Veritonic "Veritonic shares our commitment to arming brands and agencies with actionable and insightful audio performance data,” said Kevin McCaul, Global Head of Ad Operations at Acast. “Our partnership is an important step for the open ecosystem of podcasting as we continue to work together to provide independent measurement insights to prove the effectiveness and efficiency of podcasting as a marketing channel.” Veritonic’s Attribution solution enables users to glean actionable insights from top-of-the-funnel branding initiatives through bottom-of-the-funnel conversions & transactions. Through an intuitive and interactive dashboard, brands can determine which publisher and specific ads had the highest impact and use that data to optimize ad performance. About Veritonic World-renowned brands, agencies, publishers, and platforms rely on Veritonic’s comprehensive audio research and analytics platform to research, test, and measure the ROI of their audio assets and campaigns pre-market, in-market, and post-campaign. The resulting insight enables clients to gain confidence in their audio investment, mitigate risk through optimization, and increase their return as they engage consumers with compelling audio experiences. About Acast Acast is the world’s largest independent podcast company. Founded in 2014, the company has pioneered the open podcast ecosystem ever since – making podcasts available on any listening platform. Acast provides a marketplace, helping podcasters find the right audience to monetize their content. When our podcasters make money, we make money. Today, Acast hosts nearly 88,000 podcasts, with more than 430 million listens every month.

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