Dataiads

dataiads

As the world becomes increasingly digital, businesses across industries—from retail to finance and automotive—must handle massive volumes of data. Whether managing product catalogs, processing telemetry data, or handling financial transactions, the ability to manage and scale real-time data across multiple regions is critical for global operations. One expert leading the way in solving these data management challenges is Amey Banarse, a solutions engineer with over a decade of experience in distributed database technologies. Amey uses his expertise to solve complex data challenges, reduce costs, and improve performance. His work has led to successful collaborations with Fortune 500 enterprises, including global financial institutions like Wells Fargo and Fiserv, large retailers like Kroger, and automotive companies including General Motors, making him a prominent figure in the field. The Challenges of Data Management in the Digital Age Coordinating large amounts of information presents a unique challenge in the modern world. Technological breakthroughs like real-time analytics and machine learning have provided immense benefits, but these advancements also introduce new obstacles, such as the need for low-latency access and maintaining consistent data availability across regions. Amey Banarse shares his insights into overcoming these challenges and the journey that led him to become an expert in the field. Q: Amey, what inspired you to pursue a career in technical solutions engineering? A: My journey began with a Master’s degree from the University of Pennsylvania in 2010. I started my career as a Senior Data Analytics Consultant at Gemini Systems, New York, where I focused on data analytics platforms in the financial services sector. Collaborating with high-profile clients like the New York Stock Exchange (NYSE) to develop solutions and working on high-impact projects sparked my passion for data management. It was during my collaboration with the Financial Industry Regulatory Authority (FINRA) that I truly recognized the critical importance of robust data architecture. Today, as a recognized thought leader in the data industry, I combine deep expertise in distributed systems and cloud-native transactional applications with a commitment to advancing enterprise data innovation. I am honored to contribute to the leading forums like Forbes Technology Council sharing insights through writing, presentations, and thought leadership. My speaking engagements at premier conferences like AWS ReInvent, VMWare Explore, and SpringOne reflect my dedication to shaping industry discourse, from modern data architectures to enterprise data strategies, helping organizations unlock the full potential of their data assets. Q: As industries face the increasing demand for real-time data processing, what challenges are they encountering? A: Today’s businesses, especially in sectors and developing industries like retail, automotive and finance, must manage massive volumes of real-time data while ensuring security and scalability. Challenges include handling traffic surges during peak periods, maintaining data integrity across geographically distributed systems, and providing consistent performance. Failure to address these issues can lead to bottlenecks, data inconsistencies, and operational inefficiencies that significantly impact customer experience and revenue. Q: Can you share your approach to solving these challenges using distributed database technologies? A: Absolutely. I leverage technologies like YugabyteDB, which provides the capability to handle high-throughput transactions, maintain strong consistency, and support multi-region deployments. My focus is on designing data architecture that integrates distributed databases with cloud-native platforms, ensuring real-time data is accessible and reliable across different locations. Collaborating with engineering teams, I implement rigorous testing under simulated high-traffic conditions and fine-tune systems for optimal performance. Q: Could you elaborate on a specific project where you implemented these solutions? A: One notable project was with a global retailer managing over 300 million products. They needed a scalable system to ensure real-time data access during peak shopping periods and ensure there was no downtime during the deals and product launch days. I led the team and implemented a scalable architecture solution using YugabyteDB, which not only reduced their total cost of ownership by over $10 million but also ensured consistent high-performance operations during critical shopping seasons. This solution provides a seamless end-customer experience during the peak holiday season, which increases customer loyalty and the retailer’s brand recognition. Q: Could you elaborate on a specific project where you implemented these solutions? A: One notable project was with a global retailer managing over 300 million products. They needed a scalable system to ensure real-time data access during peak shopping periods and ensure there was no downtime during the deals and product launch days. I led the team and implemented a scalable architecture solution using YugabyteDB, which not only reduced their total cost of ownership by over $10 million but also ensured consistent high-performance operations during critical shopping seasons. This solution provides a seamless end-customer experience during the peak holiday season, which increases customer loyalty and the retailer’s brand recognition. Q: You also worked with General Motors. What challenges did they face, and how did you help them? A: General Motors’ connected car platform plays a critical role in supporting its new services by collecting and leveraging data from over 20 million connected vehicles. The platform powers features such as vehicle health tracking, remote starts, and road condition reporting through GM mobile apps and OnStar. However, the existing database powering this platform, Apache Cassandra, was becoming a bottleneck. It resulted in high operational costs, limited scalability, and performance issues, especially during peak demand. I worked closely with their technical leadership to redesign the system architecture, which can process vast amounts of telemetry data in real-time, maintain consistency, and scale efficiently. I also led the migration from Apache Cassandra to YugabyteDB. This migration resulted in a tenfold improvement in scalability and performance, enabling the system to handle up to three million writes per second while significantly reducing hardware footprint and operational costs. This transformation allowed GM to enhance its connected vehicle services and deliver a superior customer experience. Q: Can you provide an example of how you helped a financial services customer modernize their data systems? A: A significant case was when I collaborated with senior technical leadership of a large financial services company in migrating from a legacy IBM DB2 mainframe to a modern, scalable system to support a retail portfolio dashboard. By leading the transition to YugabyteDB, I established a resilient architecture that not only reduced the total cost of ownership but also improved the end customer experience. The successful migration allowed live user onboarding, creating a flexible and reliable system supporting future growth. This enabled the company to meet its primary goals of migrating away from the mainframe and leveraging cloud-native databases, which can be deployed on cloud and hybrid commodity architectures. It also helped with improved productivity—rather than being slowed down by waiting for provisioning and maintenance of DB2 on the mainframe, the application team can quickly deploy YugabyteDB anywhere, and it automatically scales as needed. Q: Your achievements in this field are impressive. What drives you to continue pushing boundaries? A: I’m motivated by the impact that scalable data platform solutions can have on mission-critical applications that power businesses and society. Leading high-profile projects on behalf of YugabyteDB, like designing a scalable platform for the Super Bowl 2024 streaming event, has been incredibly rewarding. The ability to deliver a high-quality streaming experience to over 125 million viewers underscores the importance of scalable, resilient systems in today’s interconnected world. Q: What is your vision for the future of data management? A: I believe the ingenuity of technical solutions engineers like myself is crucial for a better-connected world. As industries evolve and the demand for real-time data continues to surge, developing innovative solutions that enable organizations to scale effectively is essential. I aim to lead this charge, ensuring businesses can meet their data challenges head-on and drive success through intelligent data management strategies. Amey Banarse’s ability to architect scalable, resilient systems has allowed these businesses to modernize and handle real-time data at unprecedented scales. His expertise in distributed database technologies is shaping the future of data management and paving the way for organizations to thrive in an increasingly data-driven landscape. As the world becomes increasingly digital, businesses across industries—from retail to finance and automotive—must handle massive volumes of data. Whether managing product catalogs, processing telemetry data, or handling financial transactions, the ability to manage and scale real-time data across multiple regions is critical for global operations. One expert leading the way in solving these data management challenges is Amey Banarse, a solutions engineer with over a decade of experience in distributed database technologies. Amey uses his expertise to solve complex data challenges, reduce costs, and improve performance. His work has led to successful collaborations with Fortune 500 enterprises, including global financial institutions like Wells Fargo and Fiserv, large retailers like Kroger, and automotive companies including General Motors, making him a prominent figure in the field. The Challenges of Data Management in the Digital Age The Challenges of Data Management in the Digital Age Coordinating large amounts of information presents a unique challenge in the modern world. Technological breakthroughs like real-time analytics and machine learning have provided immense benefits, but these advancements also introduce new obstacles, such as the need for low-latency access and maintaining consistent data availability across regions. Amey Banarse shares his insights into overcoming these challenges and the journey that led him to become an expert in the field. Q: Amey, what inspired you to pursue a career in technical solutions engineering? Q: Amey, what inspired you to pursue a career in technical solutions engineering? A : My journey began with a Master’s degree from the University of Pennsylvania in 2010. I started my career as a Senior Data Analytics Consultant at Gemini Systems, New York, where I focused on data analytics platforms in the financial services sector. Collaborating with high-profile clients like the New York Stock Exchange (NYSE) to develop solutions and working on high-impact projects sparked my passion for data management. It was during my collaboration with the Financial Industry Regulatory Authority (FINRA) that I truly recognized the critical importance of robust data architecture. Today, as a recognized thought leader in the data industry, I combine deep expertise in distributed systems and cloud-native transactional applications with a commitment to advancing enterprise data innovation. I am honored to contribute to the leading forums like Forbes Technology Council sharing insights through writing, presentations, and thought leadership. My speaking engagements at premier conferences like AWS ReInvent, VMWare Explore, and SpringOne reflect my dedication to shaping industry discourse, from modern data architectures to enterprise data strategies, helping organizations unlock the full potential of their data assets. A Q: As industries face the increasing demand for real-time data processing, what challenges are they encountering? Q: As industries face the increasing demand for real-time data processing, what challenges are they encountering? A : Today’s businesses, especially in sectors and developing industries like retail, automotive and finance, must manage massive volumes of real-time data while ensuring security and scalability. Challenges include handling traffic surges during peak periods, maintaining data integrity across geographically distributed systems, and providing consistent performance. Failure to address these issues can lead to bottlenecks, data inconsistencies, and operational inefficiencies that significantly impact customer experience and revenue. A Q: Can you share your approach to solving these challenges using distributed database technologies? Q: Can you share your approach to solving these challenges using distributed database technologies? A : Absolutely. I leverage technologies like YugabyteDB , which provides the capability to handle high-throughput transactions, maintain strong consistency, and support multi-region deployments. My focus is on designing data architecture that integrates distributed databases with cloud-native platforms, ensuring real-time data is accessible and reliable across different locations. Collaborating with engineering teams, I implement rigorous testing under simulated high-traffic conditions and fine-tune systems for optimal performance. A YugabyteDB YugabyteDB Q: Could you elaborate on a specific project where you implemented these solutions? Q: Could you elaborate on a specific project where you implemented these solutions? A : One notable project was with a global retailer managing over 300 million products. They needed a scalable system to ensure real-time data access during peak shopping periods and ensure there was no downtime during the deals and product launch days. I led the team and implemented a scalable architecture solution using YugabyteDB, which not only reduced their total cost of ownership by over $10 million but also ensured consistent high-performance operations during critical shopping seasons. This solution provides a seamless end-customer experience during the peak holiday season, which increases customer loyalty and the retailer’s brand recognition. A Q: Could you elaborate on a specific project where you implemented these solutions? Q: Could you elaborate on a specific project where you implemented these solutions? A : One notable project was with a global retailer managing over 300 million products. They needed a scalable system to ensure real-time data access during peak shopping periods and ensure there was no downtime during the deals and product launch days. I led the team and implemented a scalable architecture solution using YugabyteDB, which not only reduced their total cost of ownership by over $10 million but also ensured consistent high-performance operations during critical shopping seasons. This solution provides a seamless end-customer experience during the peak holiday season, which increases customer loyalty and the retailer’s brand recognition. A Q: You also worked with General Motors. What challenges did they face, and how did you help them? Q: You also worked with General Motors. What challenges did they face, and how did you help them? A: General Motors’ connected car platform plays a critical role in supporting its new services by collecting and leveraging data from over 20 million connected vehicles . The platform powers features such as vehicle health tracking, remote starts, and road condition reporting through GM mobile apps and OnStar. However, the existing database powering this platform, Apache Cassandra, was becoming a bottleneck. It resulted in high operational costs, limited scalability, and performance issues, especially during peak demand. I worked closely with their technical leadership to redesign the system architecture, which can process vast amounts of telemetry data in real-time, maintain consistency, and scale efficiently. I also led the migration from Apache Cassandra to YugabyteDB. This migration resulted in a tenfold improvement in scalability and performance, enabling the system to handle up to three million writes per second while significantly reducing hardware footprint and operational costs. This transformation allowed GM to enhance its connected vehicle services and deliver a superior customer experience. A: 20 million connected vehicles 20 million connected vehicles Q: Can you provide an example of how you helped a financial services customer modernize their data systems? Q: Can you provide an example of how you helped a financial services customer modernize their data systems? A : A significant case was when I collaborated with senior technical leadership of a large financial services company in migrating from a legacy IBM DB2 mainframe to a modern, scalable system to support a retail portfolio dashboard. By leading the transition to YugabyteDB, I established a resilient architecture that not only reduced the total cost of ownership but also improved the end customer experience. The successful migration allowed live user onboarding, creating a flexible and reliable system supporting future growth. This enabled the company to meet its primary goals of migrating away from the mainframe and leveraging cloud-native databases, which can be deployed on cloud and hybrid commodity architectures. It also helped with improved productivity—rather than being slowed down by waiting for provisioning and maintenance of DB2 on the mainframe, the application team can quickly deploy YugabyteDB anywhere, and it automatically scales as needed. A Q: Your achievements in this field are impressive. What drives you to continue pushing boundaries? Q: Your achievements in this field are impressive. What drives you to continue pushing boundaries? A : I’m motivated by the impact that scalable data platform solutions can have on mission-critical applications that power businesses and society. Leading high-profile projects on behalf of YugabyteDB, like designing a scalable platform for the Super Bowl 2024 streaming event, has been incredibly rewarding. The ability to deliver a high-quality streaming experience to over 125 million viewers underscores the importance of scalable, resilient systems in today’s interconnected world. A Q: What is your vision for the future of data management? Q: What is your vision for the future of data management? A : I believe the ingenuity of technical solutions engineers like myself is crucial for a better-connected world. As industries evolve and the demand for real-time data continues to surge, developing innovative solutions that enable organizations to scale effectively is essential. I aim to lead this charge, ensuring businesses can meet their data challenges head-on and drive success through intelligent data management strategies. A Amey Banarse’s ability to architect scalable, resilient systems has allowed these businesses to modernize and handle real-time data at unprecedented scales. His expertise in distributed database technologies is shaping the future of data management and paving the way for organizations to thrive in an increasingly data-driven landscape.

How Distributed Databases Power Mission-Critical Business Apps: A Case Study with Amey Banarse

Hoe verspreide databasisse missie-kritiese besigheidsprogramme bemagtig: 'n gevallestudie met Amey Banarse

Hvordan distribuerede databaser driver Mission-Critical Business Apps: A Case Study med Amey Banarse

Cómo las bases de datos distribuidas potencian las aplicaciones empresariales de misión crítica: un estudio de caso con Amey Banarse

分散データベースがミッションクリティカルなビジネスアプリを強化する方法: Amey Banarse のケーススタディ

Како се дистрибуирани базите на податоци моќни мисија-критични деловни апликации: студија на случај со Ејми Банарсе

Bagaimana Pangkalan Data Teragih Menguasakan Aplikasi Perniagaan Misi-Kritis: Kajian Kes dengan Amey Banarse

Jak rozproszone bazy danych zasilają aplikacje biznesowe o znaczeniu krytycznym: studium przypadku z Amey Banarse

Как распределенные базы данных поддерживают критически важные бизнес-приложения: пример с Эми Банарсе

Mafambisirwo Akaitwa Databases Power Mission-Critical Business Apps: Nyaya Yekudzidza naAmey Banarse

எப்படி விநியோகிக்கப்படும் தரவுத்தளங்கள் பவர் மிஷன்-கிரிட்டிகல் பிசினஸ் ஆப்ஸ்: அமே பனார்ஸுடன் ஒரு வழக்கு ஆய்வு

Чӣ гуна пойгоҳи додаҳои тақсимшуда Барномаҳои миссияи муҳими тиҷоратӣ: Омӯзиши мисол бо Ами Банарсе

ከመይ ጌሮም ዝተዘርግሑ ዳታቤዛት ንተልእኾ-ወሳኒ ንግዳዊ ኣፕስ ሓይሊ ይህቡ: መጽናዕቲ ፍጻመ ምስ ኣመይ ባናርሰ

Internationalizing Database Data Using Linked Localization Tables

In a world moving faster than ever, the demands for intuitive, developer-centric tools are reshaping the landscape. My co-founder, Guy Ben-Aharon, and I launched ChartDB not just as another database tool, but as a leap forward in how we design and interact with data. Within just three days, ChartDB took off on GitHub, amassing over 1,500 stars-an overwhelming response that shows the hunger for accessible database visualization. Star us ⭐ Why ChartDB Stands Out in a Crowded Field Developers need tools that streamline workflow without compromising on power. ChartDB does just that. By delivering an intuitive, user-friendly interface, we’ve made database visualization and management both approachable and powerful. From newcomers to database experts, ChartDB adapts to fit every level of expertise. Our community on Discord is filled with users who’ve shared how ChartDB is transforming their work, and their feedback keeps driving us forward. Built in Three Weeks, Fueled by a Vision ChartDB’s rapid development was no accident. In just three weeks, we transformed an idea into a fully functional tool, coding late nights and early mornings. And while the journey was intense, advancements in AI tools like Code Cursor and Claude 3.5 Sonnet have paved the way for even faster development. Now, we’re in a position to accelerate future builds, equipped with these groundbreaking resources that bring ideas to life at unprecedented speeds. ChartDB’s Future: What’s Next on the Horizon Our journey with ChartDB has just begun. Here’s a glimpse into what’s coming: AI-Driven Features: We’re working on AI integrations that will supercharge ChartDB’s capabilities, making database management smarter and more intuitive.
Community-Powered Growth: We’re committed to keeping open lines of communication with our community. Your input will shape ChartDB’s evolution as we continue adding features that you want.
Expanding Functionality: User suggestions are at the core of our roadmap. We’re excited to bring new features that make database design and visualization seamless. Join the Movement 🚀 If you haven’t tried ChartDB yet, now’s the time. Explore the demo, star us on GitHub, and let us know what you think. The support we’ve received fuels our ambition to innovate and set a new standard in database visualization. In our next post, we’ll share insights from our Hacker News launch, our strategies, and what we learned through the experience. Join us as we continue pushing boundaries in database technology. Shaping the Future of Development Together AI and automation aren’t just trends; they’re transforming how we approach development. Whether you’re a seasoned developer or just starting out, the possibilities are endless. Drop a comment below with your thoughts or feedback, or just say hello. Together, let’s build something incredible. Feel free to share your thoughts, feedback, or just say hello in the comments below. Let’s connect and build something amazing. In a world moving faster than ever, the demands for intuitive, developer-centric tools are reshaping the landscape. My co-founder, Guy Ben-Aharon, and I launched ChartDB not just as another database tool, but as a leap forward in how we design and interact with data. Within just three days, ChartDB took off on GitHub, amassing over 1,500 stars-an overwhelming response that shows the hunger for accessible database visualization. ChartDB Star us ⭐ Star us ⭐ Why ChartDB Stands Out in a Crowded Field Developers need tools that streamline workflow without compromising on power. ChartDB does just that. By delivering an intuitive, user-friendly interface, we’ve made database visualization and management both approachable and powerful. From newcomers to database experts, ChartDB adapts to fit every level of expertise. Our community on Discord is filled with users who’ve shared how ChartDB is transforming their work, and their feedback keeps driving us forward. ChartDB Built in Three Weeks, Fueled by a Vision ChartDB’s rapid development was no accident. In just three weeks, we transformed an idea into a fully functional tool, coding late nights and early mornings. And while the journey was intense, advancements in AI tools like Code Cursor and Claude 3.5 Sonnet have paved the way for even faster development. Now, we’re in a position to accelerate future builds, equipped with these groundbreaking resources that bring ideas to life at unprecedented speeds. ChartDB’s Future: What’s Next on the Horizon Our journey with ChartDB has just begun. Here’s a glimpse into what’s coming: AI-Driven Features: We’re working on AI integrations that will supercharge ChartDB’s capabilities, making database management smarter and more intuitive. Community-Powered Growth: We’re committed to keeping open lines of communication with our community. Your input will shape ChartDB’s evolution as we continue adding features that you want. Expanding Functionality: User suggestions are at the core of our roadmap. We’re excited to bring new features that make database design and visualization seamless. AI-Driven Features: We’re working on AI integrations that will supercharge ChartDB’s capabilities, making database management smarter and more intuitive. AI-Driven Features: Community-Powered Growth: We’re committed to keeping open lines of communication with our community. Your input will shape ChartDB’s evolution as we continue adding features that you want. Community-Powered Growth: Expanding Functionality: User suggestions are at the core of our roadmap. We’re excited to bring new features that make database design and visualization seamless. Expanding Functionality: Join the Movement 🚀 If you haven’t tried ChartDB yet, now’s the time. Explore the demo, star us on GitHub, and let us know what you think. The support we’ve received fuels our ambition to innovate and set a new standard in database visualization. In our next post, we’ll share insights from our Hacker News launch, our strategies, and what we learned through the experience. Join us as we continue pushing boundaries in database technology. Shaping the Future of Development Together AI and automation aren’t just trends; they’re transforming how we approach development. Whether you’re a seasoned developer or just starting out, the possibilities are endless. Drop a comment below with your thoughts or feedback, or just say hello. Together, let’s build something incredible. Feel free to share your thoughts, feedback, or just say hello in the comments below. Let’s connect and build something amazing. Feel free to share your thoughts, feedback, or just say hello in the comments below. Let’s connect and build something amazing.

ChartDB: Pioneering the Future of Database Visualization ✨

How to Use Docker to Template Local Database

How to Build a Database From Scratch: Understanding LSM Trees and Storage Engines (Part 1)

Architecting Scalable Databases for Large-Scale Systems

Coding Exercise: Database Migration Tool in Nodejs

What started as a tool I developed to simplify visualizing complex database schemas quickly grew into a platform that aims to help developers and data analysts alike. The vision was simple: to create an intuitive, keyboard-friendly database design tool that anyone could use, without the friction of cumbersome clicks or endless UI navigation. The tool supports both open-source languages like ERDL and DBML, giving users the flexibility to choose their preferred modeling language for designing database diagrams. Whether you're a fan of DBML's expressive syntax or prefer the simplicity of ERDL, the tool seamlessly integrates both. How It Works: User-Friendly UI/UX: Just open DatabaseDiagram.com and start typing your schema—your diagram appears instantly, making design fast and easy.
The Toolbar: Manage diagrams, import/export schemas, and share your designs with a click.
Code Editor: Type out your database schema and see your diagram take shape in real-time. The syntax is straightforward—just type, and the diagram is generated.
Visual Diagram: Zoom, pan, and navigate through your diagram effortlessly. Creating Tables and Fields: You can define tables and fields directly in the code editor. Here's the syntax to help you get started: Creating Relationships in ERDL: < one-to-many. e.g: Customer.id < Order.Id
many-to-one. e.g: Order.Id > Customer.id
one-to-one. e.g: Customer.id - Address.id
<> many-to-many. e.g: authors.id <> books.id eg. CustomerID int FK > Customer.CustomerID Import and Export Options Whether you're working with PostgreSQL or MySQL, you can import your existing scripts to instantly visualize your database. Export your diagrams to PDF, PNG, or SQL scripts to share with your team or integrate into your workflow. I’m constantly working on improving DatabaseDiagram.com, and feedback from the community has been invaluable in shaping its evolution. If you love the tool, spread the word and share your feedback! What started as a tool I developed to simplify visualizing complex database schemas quickly grew into a platform that aims to help developers and data analysts alike. The vision was simple: to create an intuitive, keyboard-friendly database design tool that anyone could use, without the friction of cumbersome clicks or endless UI navigation. visualizing complex database schemas The tool supports both open-source languages like ERDL and DBML, giving users the flexibility to choose their preferred modeling language for designing database diagrams. Whether you're a fan of DBML's expressive syntax or prefer the simplicity of ERDL, the tool seamlessly integrates both. ERDL How It Works: How It Works: User-Friendly UI/UX: Just open DatabaseDiagram.com and start typing your schema—your diagram appears instantly, making design fast and easy. The Toolbar: Manage diagrams, import/export schemas, and share your designs with a click. Code Editor: Type out your database schema and see your diagram take shape in real-time. The syntax is straightforward—just type, and the diagram is generated. Visual Diagram: Zoom, pan, and navigate through your diagram effortlessly. User-Friendly UI/UX: Just open DatabaseDiagram.com and start typing your schema—your diagram appears instantly, making design fast and easy. DatabaseDiagram.com The Toolbar: Manage diagrams, import/export schemas, and share your designs with a click. Code Editor: Type out your database schema and see your diagram take shape in real-time. The syntax is straightforward—just type, and the diagram is generated. Visual Diagram: Zoom, pan, and navigate through your diagram effortlessly. Creating Tables and Fields: Creating Tables and Fields: You can define tables and fields directly in the code editor. Here's the syntax to help you get started: Creating Relationships in ERDL: Creating Relationships in ERDL: < one-to-many. e.g: Customer.id < Order.Id many-to-one. e.g: Order.Id > Customer.id one-to-one. e.g: Customer.id - Address.id <> many-to-many. e.g: authors.id <> books.id < one-to-many. e.g: Customer.id < Order.Id many-to-one. e.g: Order.Id > Customer.id one-to-one. e.g: Customer.id - Address.id <> many-to-many. e.g: authors.id <> books.id eg. CustomerID int FK > Customer.CustomerID Import and Export Options Whether you're working with PostgreSQL or MySQL, you can import your existing scripts to instantly visualize your database. Export your diagrams to PDF, PNG, or SQL scripts to share with your team or integrate into your workflow. Import and Export Options I’m constantly working on improving DatabaseDiagram.com , and feedback from the community has been invaluable in shaping its evolution. If you love the tool, spread the word and share your feedback! DatabaseDiagram.com

Designing Database Diagrams Effortlessly with Open-Source ERDL Language

Serverless Databases in 2024: The State of Serverless Solutions for Modern Apps

The RemotiveBroker, the platform’s core component, now supports message authentication through SecOC along with E2E protection. SecOC data is automatically extracted to simplify configuration. The AUTOSAR SecOC protocol is designed to protect communication, within a vehicle, from cyber-attacks by providing integrity and authentication for messages. Message authentication in all modern automotive protocols We are thrilled to announce SecOC (Security On-board Communication) has been integrated into RemotiveBroker. SecOC is a security architecture that aims to protect the communication between the various electronic control units (ECUs) within a vehicle against cyber-attacks. SecOc Provides integrity and authentication for messages (i.e. for each signal group / PDU). The integration of SecOC into RemotiveBroker enhances message authentication across all modern automotive protocols, making it easier for automotive developers to ensure secure communication between electronic control units (ECUs). SecOC baked into your signal database The RemotiveBroker supports ARXML on top of LDF/DBC and Fibex formats. It extracts the necessary SecOC and E2E protection data to streamline the configuration process. This data is included directly in the signal database, effectively baking it into the database of your choice. This approach simplifies the correct implementation of SecOC and helps prevent developers from getting stuck during integration. [
sim_cfg.SecOc_Key("secure-ecu", b"\x00\x01\x02\x03\x00\x01\x02\x03\x00\x01\x02\x03\x00\x01\x02\x03"),
sim_cfg.SecOc_FreshnessValue("secure-ecu", b"\x00\x00\x00\x00\x00\x00\x00\x00"),
] Secure your ECUs easily using SecOC.  In RemotiveBroker, it is baked into your signal database for seamless integration and enhanced security, simplifying configuration and preventing implementation roadblocks. Commonly Asked Questions – SecOC How does SecOC work? SecOC allows the receiver of messages to detect replay attacks, verify the sender’s authenticity, verify the “freshness” of the message, and evaluate the integrity of the transmitted data. This is achieved through the Cipher-based Message Authentication Code (CMAC) and an Autosar component called the Freshness Value Manager (FVM).
What is the difference between SecOC and CMAC? SecOC utilizes CMAC as a mechanism to ensure message integrity and authenticity. The primary difference is that SecOC is a comprehensive module within the AUTOSAR framework designed exclusively for secure communication in automotive systems, while CMAC is a standard cryptographic algorithm.
Can I send “bad” SecOC packages with RemotiveBroker? Users may produce incorrect SecOC in a few different ways. First, the user may alter the freshness value to an invalid value, making the RemotiveBroker produce SecOC messages that will not pass freshness verification. For a more direct approach to sending incorrect frames, broker allows sending binary data directly, where user can set all bits and bytes manually.
What environments can I use this in? This is a standard component in RemotiveLabs platform, it can be used in-vehicle, on developers’ laptops already from early mocking as well as in CI-pipelines in the cloud. Get started with SecOC With RemotiveBroker’s 30-days free trial, you can get started easily with hardware you already have available (any Linux computer will do). Read more about RemotiveBroker here, and request a license here and try a simpler way to implement SecOC into your code. The RemotiveBroker, the platform’s core component, now supports message authentication through SecOC along with E2E protection. SecOC data is automatically extracted to simplify configuration. The AUTOSAR SecOC protocol is designed to protect communication, within a vehicle, from cyber-attacks by providing integrity and authentication for messages. Message authentication in all modern automotive protocols We are thrilled to announce SecOC (Security On-board Communication) has been integrated into RemotiveBroker. SecOC is a security architecture that aims to protect the communication between the various electronic control units (ECUs) within a vehicle against cyber-attacks. SecOc Provides integrity and authentication for messages (i.e. for each signal group / PDU). The integration of SecOC into RemotiveBroker enhances message authentication across all modern automotive protocols, making it easier for automotive developers to ensure secure communication between electronic control units (ECUs). SecOC baked into your signal database The RemotiveBroker supports ARXML on top of LDF/DBC and Fibex formats. It extracts the necessary SecOC and E2E protection data to streamline the configuration process. This data is included directly in the signal database, effectively baking it into the database of your choice. This approach simplifies the correct implementation of SecOC and helps prevent developers from getting stuck during integration. E2E protection [
sim_cfg.SecOc_Key("secure-ecu", b"\x00\x01\x02\x03\x00\x01\x02\x03\x00\x01\x02\x03\x00\x01\x02\x03"),
sim_cfg.SecOc_FreshnessValue("secure-ecu", b"\x00\x00\x00\x00\x00\x00\x00\x00"),
] [
sim_cfg.SecOc_Key("secure-ecu", b"\x00\x01\x02\x03\x00\x01\x02\x03\x00\x01\x02\x03\x00\x01\x02\x03"),
sim_cfg.SecOc_FreshnessValue("secure-ecu", b"\x00\x00\x00\x00\x00\x00\x00\x00"),
] Secure your ECUs easily using SecOC.  In RemotiveBroker, it is baked into your signal database for seamless integration and enhanced security, simplifying configuration and preventing implementation roadblocks. Secure your ECUs easily using SecOC.  In RemotiveBroker, it is baked into your signal database for seamless integration and enhanced security, simplifying configuration and preventing implementation roadblocks. Commonly Asked Questions – SecOC How does SecOC work? SecOC allows the receiver of messages to detect replay attacks, verify the sender’s authenticity, verify the “freshness” of the message, and evaluate the integrity of the transmitted data. This is achieved through the Cipher-based Message Authentication Code (CMAC) and an Autosar component called the Freshness Value Manager (FVM). What is the difference between SecOC and CMAC? SecOC utilizes CMAC as a mechanism to ensure message integrity and authenticity. The primary difference is that SecOC is a comprehensive module within the AUTOSAR framework designed exclusively for secure communication in automotive systems, while CMAC is a standard cryptographic algorithm. Can I send “bad” SecOC packages with RemotiveBroker? Users may produce incorrect SecOC in a few different ways. First, the user may alter the freshness value to an invalid value, making the RemotiveBroker produce SecOC messages that will not pass freshness verification. For a more direct approach to sending incorrect frames, broker allows sending binary data directly, where user can set all bits and bytes manually. What environments can I use this in? This is a standard component in RemotiveLabs platform, it can be used in-vehicle, on developers’ laptops already from early mocking as well as in CI-pipelines in the cloud. How does SecOC work? SecOC allows the receiver of messages to detect replay attacks, verify the sender’s authenticity, verify the “freshness” of the message, and evaluate the integrity of the transmitted data. This is achieved through the Cipher-based Message Authentication Code (CMAC) and an Autosar component called the Freshness Value Manager (FVM). How does SecOC work? What is the difference between SecOC and CMAC? SecOC utilizes CMAC as a mechanism to ensure message integrity and authenticity. The primary difference is that SecOC is a comprehensive module within the AUTOSAR framework designed exclusively for secure communication in automotive systems, while CMAC is a standard cryptographic algorithm. What is the difference between SecOC and CMAC? Can I send “bad” SecOC packages with RemotiveBroker? Users may produce incorrect SecOC in a few different ways. First, the user may alter the freshness value to an invalid value, making the RemotiveBroker produce SecOC messages that will not pass freshness verification. For a more direct approach to sending incorrect frames, broker allows sending binary data directly, where user can set all bits and bytes manually. Can I send “bad” SecOC packages with RemotiveBroker? What environments can I use this in? This is a standard component in RemotiveLabs platform, it can be used in-vehicle, on developers’ laptops already from early mocking as well as in CI-pipelines in the cloud. What environments can I use this in? Get started with SecOC With RemotiveBroker’s 30-days free trial, you can get started easily with hardware you already have available (any Linux computer will do). Read more about RemotiveBroker here , and request a license here and try a simpler way to implement SecOC into your code. here here

RemotiveLab's RemotiveBroker Now Supports SecOC Integration Directly in Signal Database

RemotiveLab's RemotiveBroker አሁን የሴክኦሲ ውህደትን በቀጥታ በሲግናል ዳታቤዝ ውስጥ ይደግፋል

El RemotiveBroker de RemotiveLab ara admet la integració de SecOC directament a la base de dades de senyal

RemotiveBroker de RemotiveLab ahora admite la integración de SecOC directamente en la base de datos de señales

रिमोटिलैब का रिमोटब्रोकर अब सिग्नल डेटाबेस में सीधे SecOC एकीकरण का समर्थन करता है

RemotiveBroker tvrtke RemotiveLab sada podržava SecOC integraciju izravno u bazu podataka signala

A RemotiveLab RemotiveBroker most támogatja a SecOC integrációt közvetlenül a jeladatbázisban

RemotiveBroker di RemotiveLab ora supporta l'integrazione SecOC direttamente nel database dei segnali

RemotiveLab の RemotiveBroker が、Signal データベースへの SecOC の直接統合をサポート

„RemotiveLab“ „RemotiveBroker“ dabar palaiko „SecOC“ integraciją tiesiogiai signalų duomenų bazėje

RemotiveBroker RemotiveLab Kini Menyokong Penyepaduan SecOC Secara Terus dalam Pangkalan Data Isyarat

RemotiveLab को RemotiveBroker अब SecOC एकीकरणलाई सिधा सिग्नल डाटाबेसमा समर्थन गर्दछ

RemotiveBroker de la RemotiveLab acceptă acum integrarea SecOC direct în baza de date de semnal

Stories, News & Mentions about DATAIADS

Dataiads’s Stories on HackerNoon