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Business Intelligence, Big Data Management

Sigma Computing Partners with Snowflake to Launch Solution on Healthcare & Life Sciences Data Cloud

Sigma Computing
Sigma Computing , the fast, intuitive-to-use alternative to traditional business intelligence (BI), announced today that it has partnered with Snowflake, the Data Cloud company, to launch a seamless integration and out-of-the-box experience for joint customers on the Snowflake Healthcare & Life Sciences Data Cloud.

The Snowflake Healthcare & Life Sciences Data Cloud offers healthcare companies a single, integrated, and cross-cloud data platform that eliminates technical and institutional data silos so that they can securely centralize, integrate, and exchange critical and sensitive data at scale. The new partnership will allow joint customers to remain compliant when using Sigma’s data exploration platform, which is purpose-built for the business user. By leveraging the Sigma and Snowflake partnership, organizations can place the power of their data directly in the hands of business users, enabling them to explore billions of data lines and freely drill down while applying their subject matter expertise for better decisions and outcomes.

“Sigma was built from the ground up to support Data Cloud users, and we’re proud to work directly with Snowflake to ensure that healthcare companies can draw greater value from their data while being able to trust that compliance is baked in. “The Healthcare & Life Sciences Data Cloud is an excellent step in streamlining cloud data adoption for this industry. In combination with tools like ours, the ecosystem will fuel faster innovations with greater data insights to deliver better patient care and drive smarter business decisions.”

Rob Woollen, CTO/Co-Founder at Sigma Computing

“Sigma's solutions align with Snowflake's own objectives to provide healthcare and life sciences companies with a simple, intuitive enterprise data platform that can deliver business insights across huge datasets with speed,” said Patrick Kovalik, Industry Principal Healthcare/Life Sciences at Snowflake. “Healthcare data has no size limit and Sigma gives a user the power of a familiar analytics interface that can interpret tens of millions of rows within a single dashboard.”

Leading Healthcare & Life Sciences organizations can leverage Sigma to take advantage of the growing quantities of data on Snowflake’s platform through a fast, simple interface that allows for faster decisions backed by data.

All organizations on the Snowflake Healthcare & Life Sciences Data Cloud can begin using Sigma with a simple one-time deployment that takes minutes. Sigma’s spreadsheet-like interface dramatically simplifies complex analytics by empowering users to build sophisticated pivot tables, quickly create and iterate dashboards, and aggregate or free-drill into billions of records.

About Sigma Computing
Sigma is the first and only cloud analytics and business intelligence solution empowering business teams to break free from the confines of the dashboard, explore live data independently, and make better, faster decisions. The award-winning platform capitalizes on the power of cloud data to combine data sources and analyze billions of rows of data instantly via an intuitive, spreadsheet interface for data analysis – no coding required.

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Guide de l’acheteur de sauvegarde moderne

Ce guide Forrester donne des indications aux décideurs IT et à leur équipe sur les fonctionnalités à rechercher et les questions à se poser pour évaluer les besoins en données propres à leur entreprise, et notamment :la protection complète ;l’automatisation et l’orchestration ;la réutilisation des données, la fiabilité et la res


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Big Data

ChaosSearch Unveils LakeDB for Live Search, SQL, and GenAI Analytics

ChaosSearch | October 13, 2023

ChaosSearch, a prominent data analytics firm, has unveiled the release of LakeDB. This offering is the world's inaugural data lake database designed to empower live Search, SQL, and Generative Artificial Intelligence (GenAI) analytics. ChaosSearch ingeniously converts cloud object storage into a live Search+SQL+GenAI analytics database with limitless hot data retention. The outcome is a unified data lake that accommodates both operational and business requirements, presenting the potential to achieve substantial cost savings of 50-80%, streamline technical resources, and simplify architectural complexities. Chaos LakeDB steps forward as the solution of choice to consolidate and process multifarious data streams and formats. It’s advanced Search + SQL and GenAI analytics satisfy a broad spectrum of operational and business demands, delivering a comprehensive platform for gleaning insights from data. Chaos LakeDB redefines data management by introducing intuitive automation into the data pipeline, schema management, and workload orchestration across a data lake backbone. Its adaptive capabilities can identify and scale stream types and schemas, ensuring data stays current and pertinent, thereby eliminating the need for continuous manual intervention. With Chaos LakeDB, users gain access to both real-time and historical insights at scale, unifying Search+SQL and GenAI across all functionalities. This ensures that every interaction with data becomes a source of actionable intelligence. By integrating seamlessly with Amazon Web Services (AWS) Amazon Simple Storage Service (Amazon S3), which is the preferred object store for millions of AWS customers, Chaos LakeDB effectively merges the extensive storage capacities of data lakes with the accessibility of cloud databases. This fusion of lake and database capabilities eradicates the need for complex extract, transform, load (ETL) and extract, load, transform (ELT) processes, delivering live analytics with enhanced cost efficiency and scalability - a vital aspect in today's data-intensive analytics and AI landscape. Chaos LakeDB is available both as a Software as a Service (SaaS) data platform for enterprises and as an embedded database for cloud platform providers. Notable industry leaders such as Cisco and Equifax have already embraced Chaos LakeDB. About ChaosSearch ChaosSearch is a prominent data analytics firm. It is at the forefront of reshaping the landscape of data analytics by providing transformative solutions that empower businesses to make data-driven decisions with unmatched efficiency. The company's LakeDB solution stands as a pioneering solution revolutionizing data lake architectures in the AI-driven era. By seamlessly converting cloud storage into a dynamic analytical database, it amalgamates diverse data streams, simplifies intricate pipelines, and delivers actionable insights at scale through Search+SQL+GenAI analytics. ChaosSearch is committed to providing tools that not only address but also anticipate the evolving needs of modern businesses.

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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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Congruity360 Delivers Intelligent Data Migrations and Storage Tiering

PR Newswire | September 27, 2023

Congruity360, a leading unstructured data management and risk mitigation provider, announces the addition of data mobility in Enterprise Insights. As unstructured data grows at the annual rate of 55% to 65% and accounts for more than 80% of all enterprise data, businesses must find a way to identify, classify and move data intelligently and automatically during its lifecycle. As enterprises grow, their valuable data must mature with their business. This may require a journey to the cloud, SLA changes which optimize storage costs, classification to mitigate risk, and moving the right data to additional key AI platform initiatives. A simple, scalable, high-performance data classification engine, Enterprise Insights delivers next-generation data lifecycle management for storage optimization, security and risk optimization, and IT business optimization. Enterprise Insights Approach to Successful Data Optimization: Identify – Securely analyze PBs of unstructured data across on premises (NAS & object) and cloud (files/objects & SaaS) sources by harnessing the power of the platform's rapid insights and auto-discover technologies, which can reduce data identification times by 1,000%. Classify – Quickly identify key client data attributes for cost savings, risk mitigation, and business impact with simple to consume dashboards and drill down capabilities. Review – Confidently create and take actions by leveraging the comprehensive search engine to quickly find and preview data for movement without ever leaving the platform. Remediate – Seamlessly take action (migrate and tier) on classified data to ensure it's properly protected, optimally stored, and most effectively serving the business. Enterprise Insights offers three use case-driven insight analysis modules: Storage and Migration Optimization – Insights into over 35 file data attributes including systems' aged, stale, obsolete, redundant, trivial, and types of systems files. Business Optimization – Insight into and classification by business units' or cost centers' aged, stale, obsolete, redundant, trivial, and types of files. Data Security and Risk Optimization – Insights into files containing PII and SPII, financial, legal, security, and risk data, as well as open shares and other network & storage security vulnerabilities. By leveraging Enterprise Insights, clients can classify data for simple and secure migration both on premise and in the cloud. Equally important is Insights data tiering capabilities, enabling users to match data storage costs to data usage. Powered by the Classify360 Platform, Enterprise Insights' secure hybrid approach to data analysis scales capabilities to exabyte levels at unmatched speed. Enterprise Insights is the industry's most powerful weapon to tackle the costs, time, and complexity of cloud migration projects, backup modernization, storage tiering, hardware refresh, and security posture management. By providing users with dashboards highlighting their existing storage costs and risks, Enterprise Insights frees clients from hidden, legacy, CapEx and OpEx expenditures, performance, and scalability bottlenecks while discovering and acting on sensitive and risk data. Unstructured data insanity is treating all data equally with zero insights into its business impact, said Brian Davidson, Chief Executive Officer and Managing Partner of Congruity360. Enterprise Insights is the first step in implementing optimized data lifecycle management. With historically high data growth and new business uses for unstructured data, it is essential to attack the costs and risks inherent in unmanaged data. Our customers have realized 7-10x returns on their data lifecycle management implementations while reducing risk in an auditable compliance framework. As AI continues to gain steam, don't overpay by moving useless data to your expensive AI platforms. The Classify360 Platform is comprehensive, simple to implement, scale, and operate. Businesses leverage the Classify360 Platform for unstructured data discovery, classification, business workflows, remediation actions, and insightful reporting. Congruity360 continues to tackle additional data governance challenges through innovations to the Classify360 Platform to continue delivering revolutionary data governance and classification, at scale, to the enterprise world. ABOUT CONGRUITY360 Congruity360 delivers the only data life cycle management solution built on a foundation of classification, by expert data storage engineers alongside expert data privacy consultants. The Classify360 Platform is easy to implement, requires no outside consultants, and quickly analyzes your data at the petabyte scale in days, not weeks or months.

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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.

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Big Data

ChaosSearch Unveils LakeDB for Live Search, SQL, and GenAI Analytics

ChaosSearch | October 13, 2023

ChaosSearch, a prominent data analytics firm, has unveiled the release of LakeDB. This offering is the world's inaugural data lake database designed to empower live Search, SQL, and Generative Artificial Intelligence (GenAI) analytics. ChaosSearch ingeniously converts cloud object storage into a live Search+SQL+GenAI analytics database with limitless hot data retention. The outcome is a unified data lake that accommodates both operational and business requirements, presenting the potential to achieve substantial cost savings of 50-80%, streamline technical resources, and simplify architectural complexities. Chaos LakeDB steps forward as the solution of choice to consolidate and process multifarious data streams and formats. It’s advanced Search + SQL and GenAI analytics satisfy a broad spectrum of operational and business demands, delivering a comprehensive platform for gleaning insights from data. Chaos LakeDB redefines data management by introducing intuitive automation into the data pipeline, schema management, and workload orchestration across a data lake backbone. Its adaptive capabilities can identify and scale stream types and schemas, ensuring data stays current and pertinent, thereby eliminating the need for continuous manual intervention. With Chaos LakeDB, users gain access to both real-time and historical insights at scale, unifying Search+SQL and GenAI across all functionalities. This ensures that every interaction with data becomes a source of actionable intelligence. By integrating seamlessly with Amazon Web Services (AWS) Amazon Simple Storage Service (Amazon S3), which is the preferred object store for millions of AWS customers, Chaos LakeDB effectively merges the extensive storage capacities of data lakes with the accessibility of cloud databases. This fusion of lake and database capabilities eradicates the need for complex extract, transform, load (ETL) and extract, load, transform (ELT) processes, delivering live analytics with enhanced cost efficiency and scalability - a vital aspect in today's data-intensive analytics and AI landscape. Chaos LakeDB is available both as a Software as a Service (SaaS) data platform for enterprises and as an embedded database for cloud platform providers. Notable industry leaders such as Cisco and Equifax have already embraced Chaos LakeDB. About ChaosSearch ChaosSearch is a prominent data analytics firm. It is at the forefront of reshaping the landscape of data analytics by providing transformative solutions that empower businesses to make data-driven decisions with unmatched efficiency. The company's LakeDB solution stands as a pioneering solution revolutionizing data lake architectures in the AI-driven era. By seamlessly converting cloud storage into a dynamic analytical database, it amalgamates diverse data streams, simplifies intricate pipelines, and delivers actionable insights at scale through Search+SQL+GenAI analytics. ChaosSearch is committed to providing tools that not only address but also anticipate the evolving needs of modern businesses.

Read More

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.

Read More

Big Data Management

Congruity360 Delivers Intelligent Data Migrations and Storage Tiering

PR Newswire | September 27, 2023

Congruity360, a leading unstructured data management and risk mitigation provider, announces the addition of data mobility in Enterprise Insights. As unstructured data grows at the annual rate of 55% to 65% and accounts for more than 80% of all enterprise data, businesses must find a way to identify, classify and move data intelligently and automatically during its lifecycle. As enterprises grow, their valuable data must mature with their business. This may require a journey to the cloud, SLA changes which optimize storage costs, classification to mitigate risk, and moving the right data to additional key AI platform initiatives. A simple, scalable, high-performance data classification engine, Enterprise Insights delivers next-generation data lifecycle management for storage optimization, security and risk optimization, and IT business optimization. Enterprise Insights Approach to Successful Data Optimization: Identify – Securely analyze PBs of unstructured data across on premises (NAS & object) and cloud (files/objects & SaaS) sources by harnessing the power of the platform's rapid insights and auto-discover technologies, which can reduce data identification times by 1,000%. Classify – Quickly identify key client data attributes for cost savings, risk mitigation, and business impact with simple to consume dashboards and drill down capabilities. Review – Confidently create and take actions by leveraging the comprehensive search engine to quickly find and preview data for movement without ever leaving the platform. Remediate – Seamlessly take action (migrate and tier) on classified data to ensure it's properly protected, optimally stored, and most effectively serving the business. Enterprise Insights offers three use case-driven insight analysis modules: Storage and Migration Optimization – Insights into over 35 file data attributes including systems' aged, stale, obsolete, redundant, trivial, and types of systems files. Business Optimization – Insight into and classification by business units' or cost centers' aged, stale, obsolete, redundant, trivial, and types of files. Data Security and Risk Optimization – Insights into files containing PII and SPII, financial, legal, security, and risk data, as well as open shares and other network & storage security vulnerabilities. By leveraging Enterprise Insights, clients can classify data for simple and secure migration both on premise and in the cloud. Equally important is Insights data tiering capabilities, enabling users to match data storage costs to data usage. Powered by the Classify360 Platform, Enterprise Insights' secure hybrid approach to data analysis scales capabilities to exabyte levels at unmatched speed. Enterprise Insights is the industry's most powerful weapon to tackle the costs, time, and complexity of cloud migration projects, backup modernization, storage tiering, hardware refresh, and security posture management. By providing users with dashboards highlighting their existing storage costs and risks, Enterprise Insights frees clients from hidden, legacy, CapEx and OpEx expenditures, performance, and scalability bottlenecks while discovering and acting on sensitive and risk data. Unstructured data insanity is treating all data equally with zero insights into its business impact, said Brian Davidson, Chief Executive Officer and Managing Partner of Congruity360. Enterprise Insights is the first step in implementing optimized data lifecycle management. With historically high data growth and new business uses for unstructured data, it is essential to attack the costs and risks inherent in unmanaged data. Our customers have realized 7-10x returns on their data lifecycle management implementations while reducing risk in an auditable compliance framework. As AI continues to gain steam, don't overpay by moving useless data to your expensive AI platforms. The Classify360 Platform is comprehensive, simple to implement, scale, and operate. Businesses leverage the Classify360 Platform for unstructured data discovery, classification, business workflows, remediation actions, and insightful reporting. Congruity360 continues to tackle additional data governance challenges through innovations to the Classify360 Platform to continue delivering revolutionary data governance and classification, at scale, to the enterprise world. ABOUT CONGRUITY360 Congruity360 delivers the only data life cycle management solution built on a foundation of classification, by expert data storage engineers alongside expert data privacy consultants. The Classify360 Platform is easy to implement, requires no outside consultants, and quickly analyzes your data at the petabyte scale in days, not weeks or months.

Read More

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.

Read More

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Spotlight

Guide de l’acheteur de sauvegarde moderne

Ce guide Forrester donne des indications aux décideurs IT et à leur équipe sur les fonctionnalités à rechercher et les questions à se poser pour évaluer les besoins en données propres à leur entreprise, et notamment :la protection complète ;l’automatisation et l’orchestration ;la réutilisation des données, la fiabilité et la res

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