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Tetra Tech Expands High-end Climate Data Analytics Solutions with Acquisition of Axiom Data Science

Tetra Tech, Inc. , a leading provider of high-end consulting and engineering services, announced today that it has acquired Axiom Data Science, an industry leader in the management and analysis of oceanic and ecological data associated with climate change. Headquartered in Anchorage, Alaska, Axiom conducts climate science modeling to help clients manage, integrate, and visualize large-scale complex data sets that are essential to addressing climate change.

“Tetra Tech leverages digital technology using our Leading with Science® approach to provide clients with sustainable and resilient solutions and support decision-making on projects around the world. The addition of Axiom Data Science expands our high-end advanced analytics capabilities in oceans and ecosystems to advance climate science for clients, including the National Oceanic and Atmospheric Administration and the National Aeronautics and Space Administration.”

Dan Batrack, Tetra Tech Chairman and CEO

Rob Bochenek, Axiom Founder and CEO, said, “We are honored to join Tetra Tech and work with their exceptional team of scientists and engineers to provide best-in-class data analytics solutions to address climate change impacts. By joining Tetra Tech, we will further enhance our ability to provide highly specialized solutions to our clients, while offering new opportunities for our employees to work on water and environment programs worldwide.”

The terms of the acquisition were not disclosed. Axiom Data Science is joining Tetra Tech’s Government Services Group.

About Tetra Tech
Tetra Tech is a leading provider of high-end consulting and engineering services for projects worldwide. With 21,000 associates working together, Tetra Tech provides clear solutions to complex problems in water, environment, sustainable infrastructure, renewable energy, and international development. We are Leading with Science® to provide sustainable and resilient solutions for our clients. For more information about Tetra Tech, please visit tetratech.com or follow us on LinkedIn, Twitter, and Facebook.

About Axiom Data Science
Based in Anchorage, Alaska, Axiom Data Science is an informatics and software development firm focused on developing scalable solutions for data management, integration, and visualization. Axiom supports federal, private, academic, and non-governmental organizations in the ecological, geological, and ocean sciences organizations to improve the long-term management and impact of their scientific data resources.

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Ocient's Report Reveals Surge in Hyperscale Data's Impact on Firms

Ocient | September 25, 2023

Ocient, a renowned hyperscale data analytics platform, has recently announced the release of its second annual industry report, titled "Beyond Big Data: Hyperscale Takes Flight." The 2023 report, which is the result of a survey conducted among 500 data and IT leaders responsible for managing data workloads exceeding 150 terabytes, sheds light on the escalating significance of hyperscale data management within enterprises. It also underscores the critical requisites of time, talent, and cutting-edge technology necessary for the effective harnessing of data at scale. Building on the foundation of Ocient's inaugural Beyond Big Data survey, the 2023 report delves into the minds of IT decision-makers, seeking to unravel the challenges, investment priorities, and future prospects occupying the forefront of their agendas for 2023 and beyond. The report offers valuable year-over-year comparisons, drawing on trends identified in 2022 while also presenting fresh, timely insights that mirror the immediate concerns of enterprise leaders in the United States. Among the pivotal insights featured in this year's report are the following: Immediate Emphasis on Data Quality: Organizations committed to leveraging their hyperscale data for critical business decisions are placing paramount importance on ensuring the highest data quality standards. Data Workload Growth as a Driving Force: Data and IT leaders are increasingly recognizing data warehousing and analytics as pivotal elements of their IT strategies, a sentiment vividly reflected in their budget allocations. AI Readiness at the Forefront: Leaders are eager participants in the AI revolution, yet they grapple with concerns surrounding security, accuracy, and trust. Innovation Hindered by Talent and Technology Gaps: Many leaders continue to struggle with the challenges of optimizing their toolsets and scaling their teams swiftly enough to meet the demands posed by hyperscale data volumes. Stephen Catanzano, Senior Analyst, Enterprise Strategy Group, commented: It's clear enterprises are investing in data analytics and warehousing, especially given their costs are being driven up so high with older systems that can't handle the data that's being pushed to them. [Source – Business Wire] Chris Gladwin, Co-Founder and CEO of Ocient, stated that data was not slowing down, and he emphasized that the results of the 2023 Beyond Big Data report confirmed the significance of hyperscale data workloads for enterprises across various industries. He also noted that data volumes were on the rise, as was the importance of comprehending one's data. Nevertheless, the challenges related to data quality, the proliferation of tools, and staffing constraints persisted and were impeding progress in the industry. Furthermore, Gladwin mentioned that the frontier beyond big data had arrived and that Ocient's annual report illustrated the challenges and opportunities that were shaping the enterprise data strategies of the future. About Ocient Ocient is a pioneering hyperscale data analytics solutions company dedicated to empowering organizations to unlock substantial value through the analysis of trillions of data records, achieving performance levels and cost efficiencies previously deemed unattainable. The company is entrusted by leading organizations around the globe to leverage the expertise of its industry professionals in crafting and implementing sophisticated solutions. These solutions not only enable the rapid exploration of new revenue avenues but also streamline operational processes and enhance security measures, all while managing five to 10 times more data and significantly reducing storage requirements by up to 80%.

Big Data Management

EDB Acquires Splitgraph for Data Lake and Data Warehousing Capabilities

GlobeNewswire | October 25, 2023

EnterpriseDB (“EDB”), the leader in accelerating Postgres in the enterprise, today announced its acquisition of Splitgraph, an early-stage disruptor that provides a Postgres compatible serverless SQL API for building data driven applications from hundreds of datasources. This move is seen as a meaningful step in EDB's evolution, underscoring its commitment to delivering Postgres solutions to the ever evolving challenges customers face across a diverse data landscape. Acquiring Splitgraph advances our capabilities within the realm of analytics and AI, said Kevin Dallas, CEO, EDB. With Splitgraph's technology and deep expertise, we're taking a leap in making data lake and data warehousing operations more efficient, streamlined, and collaborative. Unifying our shared commitment to customer-driven product development, we can accelerate our progress and better address the intricate data challenges that our customers encounter. Miles Richardson, Co-Founder of Splitgraph, echoed Dallas’s sentiments, "We are pleased to share EDB’s vision to transform the way organizations engage with data using Postgres, especially for analytics workloads and AI-driven use cases. Becoming a part of EDB unlocks exciting new possibilities for our technology, further advancing the ways in which companies look to Postgres to solve their data ecosystem challenges.” With the acquisition of Splitgraph, EDB underscores its dedication to innovating within the Postgres ecosystem, directly addressing the needs of users who want to seamlessly run analytical queries across diverse data sets. Splitgraph enhances this core capability by enriching data integration, cataloging, and governance, streamlining the management of both in-house data and information sourced from open publishers through a single Postgres interface. This strategic move firmly establishes EDB's commitment to continually elevate the value it delivers to its customers throughout the data landscape. About EDB EDB provides enterprise-grade software and services that enable organizations to harness the full power of Postgres, the world’s leading open source database. EDB provides unmatched Postgres database expertise, and enables the same Postgres everywhere, including solutions for hybrid, self-managed private clouds, and EDB BigAnimal, a fully managed cloud database-as-a-service. EDB serves more than 1,500 customers globally, including leading government agencies, financial services, media and information technology companies. As the leading contributor to the vibrant and fast-growing Postgres community, EDB is committed to driving technology innovation. Through its solutions for high availability, reliability, security, 24x7 global support and advanced professional services, EDB empowers enterprises to control risk, manage costs and scale efficiently. For more information, visit www.enterprisedb.com. EnterpriseDB and EDB are registered trademarks and BigAnimal is a trademark of EnterpriseDB Corporation; Oracle is a registered trademark of Oracle Corporation. Postgres and PostgreSQL are registered trademarks of the PostgreSQL Community Association of Canada and used with their permission. All other trademarks are owned by their respective owners. About Splitgraph Splitgraph is a serverless data platform where you can query, upload, connect and share tables of data. It's built on Postgres and optimized for analytical queries over versioned snapshots and external data tables. Splitgraph develops Seafowl, an open source serverless OLAP database optimized for building data-driven Web apps, and also recently released a ChatGPT plugin for querying its catalog of open data with natural language.

Business Intelligence

Dremio Launches Next-gen Reflections Redefining SQL Query Acceleration

Dremio | September 15, 2023

Dremio, a renowned easy and open data lakehouse solution provider, has recently introduced its next-gen Reflections technology, marking a transformative milestone in SQL query acceleration. Dremio Reflections facilitate sub-second analytics performance across an organization's entire data ecosystem, irrespective of data location. This groundbreaking technology is redefining data access and analysis, ensuring that valuable insights are derived efficiently and swiftly, all while reducing costs to merely one-third of a typical cloud data warehouse. Reflections represent Dremio's innovative SQL query acceleration technology. Queries that leverage Reflections exhibit performance gains ranging from 10 to 100 times faster than their non-accelerated counterparts. This latest release introduces the Dremio Reflection Recommender, a pioneering feature that empowers users to accelerate Business Intelligence workloads in a matter of seconds. The Reflection Recommender automatically evaluates an organization's SQL queries and generates recommended Reflections to accelerate them. Tomer Shiran, founder of Dremio, commented, Dremio Reflections accelerate SQL queries by orders of magnitude, eliminating the need for BI extracts/imports and enabling companies to run their most mission-critical BI workloads directly on a lakehouse. With automatic recommendations and next-generation incremental updates, we've made it even easier for organizations to take advantage of this innovative technology. [Source: Business Wire] Reflection Recommender eliminates the need for labor-intensive manual data and workload analysis, making the process of obtaining the fastest and most intelligent query results effortless, requiring only a few simple actions. The user-friendly nature of the Reflection Recommender puts advanced query acceleration capabilities within the reach of all users, significantly saving both time and expenses. Dremio has also refined the process of refreshing Reflections to further bolster query performance and drive cost efficiencies. It now intelligently refreshes Reflections on Apache Iceberg tables, promptly capturing incremental data changes. This innovative approach obviates the requirement for complete data refreshes, resulting in speedier updates and reduced compute expenses. Dremio Reflections eliminates the need for data teams to export data from the data lakehouse into BI extracts or imports for analytical reasons and overcomes performance bottlenecks for BI dashboards and reports. In addition, Reflections negate the necessity of creating precomputed tables within the data lake or data warehouse to achieve sub-second performance for BI workloads, reducing the workload and complexity for data teams. About Dremio Dremio is a leading, easy and open data lakehouse solution provider, offering organizations the versatility of self-service analytics coupled with the functionality of a data warehouse and the flexibility of a data lake. Dremio's platform empowers users to harness the lightning-fast SQL query service alongside various processing engines, all on the same dataset. The company distinguishes itself through a pioneering data-as-code methodology akin to Git, which facilitates data experimentation, version control, and governance. This innovative approach enhances agility and empowers organizations to explore and manage their data resources with unprecedented efficiency. Furthermore, Dremio offers a fully managed service that expedites organizations' entry into analytics, allowing them to commence their data-driven journey within minutes.

Big Data Management

Kinetica Redefines Real-Time Analytics with Native LLM Integration

Kinetica | September 22, 2023

Kinetica, a renowned speed layer for generative AI and real-time analytics, has recently unveiled a native Large Language Model (LLM) integrated with Kinetica's innovative architecture. This empowers users to perform ad-hoc data analysis on real-time, structured data with the ease of natural language, all without the need for external API calls and without data ever leaving the secure confines of the customer's environment. This significant milestone follows Kinetica's prior innovation as the first analytic database to integrate with OpenAI. Amid the LLM fervor, enterprises and government agencies are actively seeking inventive ways to automate various business functions while safeguarding sensitive information that could be exposed through fine-tuning or prompt augmentation. Public LLMs, exemplified by OpenAI's GPT 3.5, raise valid concerns regarding privacy and security. These concerns are effectively mitigated through native offerings, seamlessly integrated into the Kinetica deployment, and securely nestled within the customer's network perimeter. Beyond its superior security features, Kinetica's native LLM is finely tuned to the syntax and industry-specific data definitions, spanning domains such as telecommunications, automotive, financial services, logistics, and more. This tailored approach ensures the generation of more reliable and precise SQL queries. Notably, this capability extends beyond conventional SQL, enabling efficient handling of intricate tasks essential for enhanced decision-making capabilities, particularly for time-series, graph, and spatial inquiries. Kinetica's approach to fine-tuning places emphasis on optimizing SQL generation to deliver consistent and accurate results, in stark contrast to more conventional methods that prioritize creativity but yield diverse and unpredictable responses. This steadfast commitment to reliable SQL query outcomes offers businesses and users the peace of mind they deserve. Illustrating the practical impact of this innovation, the US Air Force has been collaborating closely with Kinetica to leverage advanced analytics on sensor data, enabling swift identification and response to potential threats. This partnership contributes significantly to the safety and security of the national airspace system. The US Air Force now employs Kinetica's embedded LLM to detect airspace threats and anomalies using natural language. Kinetica's database excels in converting natural language queries into SQL, delivering responses in mere seconds, even when faced with complex or unfamiliar questions. Furthermore, Kinetica seamlessly combines various analytics modes, including time series, spatial, graph, and machine learning, thereby expanding the range of queries it can effectively address. What truly enables Kinetica to excel in conversational query processing is its ingenious use of native vectorization. In a vectorized query engine, data is organized into fixed-size blocks called vectors, enabling parallel query operations on these vectors. This stands in contrast to traditional approaches that process individual data elements sequentially. The result is significantly accelerated query execution, all within a smaller compute footprint. This remarkable speed is made possible by the utilization of GPUs and the latest CPU advancements, which enable simultaneous calculations on multiple data elements, thereby greatly enhancing the processing speed of computation-intensive tasks across multiple cores or threads. About Kinetica Kinetica is a pioneering company at the forefront of real-time analytics and is the creator of the groundbreaking real-time analytical database specially designed for sensor and machine data. The company offers native vectorized analytics capabilities in the fields of generative AI, spatial analysis, time-series modeling, and graph processing. A distinguished array of the world's largest enterprises spanning diverse sectors, including the public sector, financial services, telecommunications, energy, healthcare, retail, and automotive industries, entrusts Kinetica to forge novel solutions in the realms of time-series data and spatial analysis. The company's clientele includes various illustrious organizations such as the US Air Force, Citibank, Ford, T-Mobile, and numerous others.

Big Data Management

Ocient's Report Reveals Surge in Hyperscale Data's Impact on Firms

Ocient | September 25, 2023

Ocient, a renowned hyperscale data analytics platform, has recently announced the release of its second annual industry report, titled "Beyond Big Data: Hyperscale Takes Flight." The 2023 report, which is the result of a survey conducted among 500 data and IT leaders responsible for managing data workloads exceeding 150 terabytes, sheds light on the escalating significance of hyperscale data management within enterprises. It also underscores the critical requisites of time, talent, and cutting-edge technology necessary for the effective harnessing of data at scale. Building on the foundation of Ocient's inaugural Beyond Big Data survey, the 2023 report delves into the minds of IT decision-makers, seeking to unravel the challenges, investment priorities, and future prospects occupying the forefront of their agendas for 2023 and beyond. The report offers valuable year-over-year comparisons, drawing on trends identified in 2022 while also presenting fresh, timely insights that mirror the immediate concerns of enterprise leaders in the United States. Among the pivotal insights featured in this year's report are the following: Immediate Emphasis on Data Quality: Organizations committed to leveraging their hyperscale data for critical business decisions are placing paramount importance on ensuring the highest data quality standards. Data Workload Growth as a Driving Force: Data and IT leaders are increasingly recognizing data warehousing and analytics as pivotal elements of their IT strategies, a sentiment vividly reflected in their budget allocations. AI Readiness at the Forefront: Leaders are eager participants in the AI revolution, yet they grapple with concerns surrounding security, accuracy, and trust. Innovation Hindered by Talent and Technology Gaps: Many leaders continue to struggle with the challenges of optimizing their toolsets and scaling their teams swiftly enough to meet the demands posed by hyperscale data volumes. Stephen Catanzano, Senior Analyst, Enterprise Strategy Group, commented: It's clear enterprises are investing in data analytics and warehousing, especially given their costs are being driven up so high with older systems that can't handle the data that's being pushed to them. [Source – Business Wire] Chris Gladwin, Co-Founder and CEO of Ocient, stated that data was not slowing down, and he emphasized that the results of the 2023 Beyond Big Data report confirmed the significance of hyperscale data workloads for enterprises across various industries. He also noted that data volumes were on the rise, as was the importance of comprehending one's data. Nevertheless, the challenges related to data quality, the proliferation of tools, and staffing constraints persisted and were impeding progress in the industry. Furthermore, Gladwin mentioned that the frontier beyond big data had arrived and that Ocient's annual report illustrated the challenges and opportunities that were shaping the enterprise data strategies of the future. About Ocient Ocient is a pioneering hyperscale data analytics solutions company dedicated to empowering organizations to unlock substantial value through the analysis of trillions of data records, achieving performance levels and cost efficiencies previously deemed unattainable. The company is entrusted by leading organizations around the globe to leverage the expertise of its industry professionals in crafting and implementing sophisticated solutions. These solutions not only enable the rapid exploration of new revenue avenues but also streamline operational processes and enhance security measures, all while managing five to 10 times more data and significantly reducing storage requirements by up to 80%.

Big Data Management

EDB Acquires Splitgraph for Data Lake and Data Warehousing Capabilities

GlobeNewswire | October 25, 2023

EnterpriseDB (“EDB”), the leader in accelerating Postgres in the enterprise, today announced its acquisition of Splitgraph, an early-stage disruptor that provides a Postgres compatible serverless SQL API for building data driven applications from hundreds of datasources. This move is seen as a meaningful step in EDB's evolution, underscoring its commitment to delivering Postgres solutions to the ever evolving challenges customers face across a diverse data landscape. Acquiring Splitgraph advances our capabilities within the realm of analytics and AI, said Kevin Dallas, CEO, EDB. With Splitgraph's technology and deep expertise, we're taking a leap in making data lake and data warehousing operations more efficient, streamlined, and collaborative. Unifying our shared commitment to customer-driven product development, we can accelerate our progress and better address the intricate data challenges that our customers encounter. Miles Richardson, Co-Founder of Splitgraph, echoed Dallas’s sentiments, "We are pleased to share EDB’s vision to transform the way organizations engage with data using Postgres, especially for analytics workloads and AI-driven use cases. Becoming a part of EDB unlocks exciting new possibilities for our technology, further advancing the ways in which companies look to Postgres to solve their data ecosystem challenges.” With the acquisition of Splitgraph, EDB underscores its dedication to innovating within the Postgres ecosystem, directly addressing the needs of users who want to seamlessly run analytical queries across diverse data sets. Splitgraph enhances this core capability by enriching data integration, cataloging, and governance, streamlining the management of both in-house data and information sourced from open publishers through a single Postgres interface. This strategic move firmly establishes EDB's commitment to continually elevate the value it delivers to its customers throughout the data landscape. About EDB EDB provides enterprise-grade software and services that enable organizations to harness the full power of Postgres, the world’s leading open source database. EDB provides unmatched Postgres database expertise, and enables the same Postgres everywhere, including solutions for hybrid, self-managed private clouds, and EDB BigAnimal, a fully managed cloud database-as-a-service. EDB serves more than 1,500 customers globally, including leading government agencies, financial services, media and information technology companies. As the leading contributor to the vibrant and fast-growing Postgres community, EDB is committed to driving technology innovation. Through its solutions for high availability, reliability, security, 24x7 global support and advanced professional services, EDB empowers enterprises to control risk, manage costs and scale efficiently. For more information, visit www.enterprisedb.com. EnterpriseDB and EDB are registered trademarks and BigAnimal is a trademark of EnterpriseDB Corporation; Oracle is a registered trademark of Oracle Corporation. Postgres and PostgreSQL are registered trademarks of the PostgreSQL Community Association of Canada and used with their permission. All other trademarks are owned by their respective owners. About Splitgraph Splitgraph is a serverless data platform where you can query, upload, connect and share tables of data. It's built on Postgres and optimized for analytical queries over versioned snapshots and external data tables. Splitgraph develops Seafowl, an open source serverless OLAP database optimized for building data-driven Web apps, and also recently released a ChatGPT plugin for querying its catalog of open data with natural language.

Business Intelligence

Dremio Launches Next-gen Reflections Redefining SQL Query Acceleration

Dremio | September 15, 2023

Dremio, a renowned easy and open data lakehouse solution provider, has recently introduced its next-gen Reflections technology, marking a transformative milestone in SQL query acceleration. Dremio Reflections facilitate sub-second analytics performance across an organization's entire data ecosystem, irrespective of data location. This groundbreaking technology is redefining data access and analysis, ensuring that valuable insights are derived efficiently and swiftly, all while reducing costs to merely one-third of a typical cloud data warehouse. Reflections represent Dremio's innovative SQL query acceleration technology. Queries that leverage Reflections exhibit performance gains ranging from 10 to 100 times faster than their non-accelerated counterparts. This latest release introduces the Dremio Reflection Recommender, a pioneering feature that empowers users to accelerate Business Intelligence workloads in a matter of seconds. The Reflection Recommender automatically evaluates an organization's SQL queries and generates recommended Reflections to accelerate them. Tomer Shiran, founder of Dremio, commented, Dremio Reflections accelerate SQL queries by orders of magnitude, eliminating the need for BI extracts/imports and enabling companies to run their most mission-critical BI workloads directly on a lakehouse. With automatic recommendations and next-generation incremental updates, we've made it even easier for organizations to take advantage of this innovative technology. [Source: Business Wire] Reflection Recommender eliminates the need for labor-intensive manual data and workload analysis, making the process of obtaining the fastest and most intelligent query results effortless, requiring only a few simple actions. The user-friendly nature of the Reflection Recommender puts advanced query acceleration capabilities within the reach of all users, significantly saving both time and expenses. Dremio has also refined the process of refreshing Reflections to further bolster query performance and drive cost efficiencies. It now intelligently refreshes Reflections on Apache Iceberg tables, promptly capturing incremental data changes. This innovative approach obviates the requirement for complete data refreshes, resulting in speedier updates and reduced compute expenses. Dremio Reflections eliminates the need for data teams to export data from the data lakehouse into BI extracts or imports for analytical reasons and overcomes performance bottlenecks for BI dashboards and reports. In addition, Reflections negate the necessity of creating precomputed tables within the data lake or data warehouse to achieve sub-second performance for BI workloads, reducing the workload and complexity for data teams. About Dremio Dremio is a leading, easy and open data lakehouse solution provider, offering organizations the versatility of self-service analytics coupled with the functionality of a data warehouse and the flexibility of a data lake. Dremio's platform empowers users to harness the lightning-fast SQL query service alongside various processing engines, all on the same dataset. The company distinguishes itself through a pioneering data-as-code methodology akin to Git, which facilitates data experimentation, version control, and governance. This innovative approach enhances agility and empowers organizations to explore and manage their data resources with unprecedented efficiency. Furthermore, Dremio offers a fully managed service that expedites organizations' entry into analytics, allowing them to commence their data-driven journey within minutes.

Big Data Management

Kinetica Redefines Real-Time Analytics with Native LLM Integration

Kinetica | September 22, 2023

Kinetica, a renowned speed layer for generative AI and real-time analytics, has recently unveiled a native Large Language Model (LLM) integrated with Kinetica's innovative architecture. This empowers users to perform ad-hoc data analysis on real-time, structured data with the ease of natural language, all without the need for external API calls and without data ever leaving the secure confines of the customer's environment. This significant milestone follows Kinetica's prior innovation as the first analytic database to integrate with OpenAI. Amid the LLM fervor, enterprises and government agencies are actively seeking inventive ways to automate various business functions while safeguarding sensitive information that could be exposed through fine-tuning or prompt augmentation. Public LLMs, exemplified by OpenAI's GPT 3.5, raise valid concerns regarding privacy and security. These concerns are effectively mitigated through native offerings, seamlessly integrated into the Kinetica deployment, and securely nestled within the customer's network perimeter. Beyond its superior security features, Kinetica's native LLM is finely tuned to the syntax and industry-specific data definitions, spanning domains such as telecommunications, automotive, financial services, logistics, and more. This tailored approach ensures the generation of more reliable and precise SQL queries. Notably, this capability extends beyond conventional SQL, enabling efficient handling of intricate tasks essential for enhanced decision-making capabilities, particularly for time-series, graph, and spatial inquiries. Kinetica's approach to fine-tuning places emphasis on optimizing SQL generation to deliver consistent and accurate results, in stark contrast to more conventional methods that prioritize creativity but yield diverse and unpredictable responses. This steadfast commitment to reliable SQL query outcomes offers businesses and users the peace of mind they deserve. Illustrating the practical impact of this innovation, the US Air Force has been collaborating closely with Kinetica to leverage advanced analytics on sensor data, enabling swift identification and response to potential threats. This partnership contributes significantly to the safety and security of the national airspace system. The US Air Force now employs Kinetica's embedded LLM to detect airspace threats and anomalies using natural language. Kinetica's database excels in converting natural language queries into SQL, delivering responses in mere seconds, even when faced with complex or unfamiliar questions. Furthermore, Kinetica seamlessly combines various analytics modes, including time series, spatial, graph, and machine learning, thereby expanding the range of queries it can effectively address. What truly enables Kinetica to excel in conversational query processing is its ingenious use of native vectorization. In a vectorized query engine, data is organized into fixed-size blocks called vectors, enabling parallel query operations on these vectors. This stands in contrast to traditional approaches that process individual data elements sequentially. The result is significantly accelerated query execution, all within a smaller compute footprint. This remarkable speed is made possible by the utilization of GPUs and the latest CPU advancements, which enable simultaneous calculations on multiple data elements, thereby greatly enhancing the processing speed of computation-intensive tasks across multiple cores or threads. About Kinetica Kinetica is a pioneering company at the forefront of real-time analytics and is the creator of the groundbreaking real-time analytical database specially designed for sensor and machine data. The company offers native vectorized analytics capabilities in the fields of generative AI, spatial analysis, time-series modeling, and graph processing. A distinguished array of the world's largest enterprises spanning diverse sectors, including the public sector, financial services, telecommunications, energy, healthcare, retail, and automotive industries, entrusts Kinetica to forge novel solutions in the realms of time-series data and spatial analysis. The company's clientele includes various illustrious organizations such as the US Air Force, Citibank, Ford, T-Mobile, and numerous others.

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