StarRocks Integrations

MySQL stands out as the most widely used open source database globally. Thanks to its established track record in performance, dependability, and user-friendliness, it has emerged as the preferred database for web applications, powering notable platforms such as Facebook, Twitter, and YouTube, alongside the top five websites. Furthermore, MySQL is also highly favored as an embedded database solution, being distributed by numerous independent software vendors and original equipment manufacturers. Its versatility and robust features contribute to its widespread adoption across various industries.

Amazon Simple Storage Service (Amazon S3) is a versatile object storage solution that provides exceptional scalability, data availability, security, and performance. It accommodates clients from various sectors, enabling them to securely store and manage any volume of data for diverse applications, including data lakes, websites, mobile apps, backups, archiving, enterprise software, IoT devices, and big data analytics. With user-friendly management tools, Amazon S3 allows users to effectively organize their data and set tailored access permissions to satisfy their unique business, organizational, and compliance needs. Offering an impressive durability rate of 99.999999999% (11 nines), it supports millions of applications for businesses globally. Businesses can easily adjust their storage capacity to match changing demands without needing upfront investments or lengthy resource acquisition processes. Furthermore, the high durability ensures that data remains safe and accessible, contributing to operational resilience and peace of mind for organizations.

LeetCode stands out as an exceptional platform designed to refine your abilities, broaden your understanding, and equip you for technical interviews. The Explore feature serves as a well-structured tool that optimizes your experience on LeetCode, offering a clear pathway for advancing your programming career. With over 1900 practice questions available, users can immerse themselves in a wealth of coding challenges. Join one of the largest tech communities, where hundreds of thousands of active members engage in contests that not only test their skills but also provide opportunities for earning rewards. LeetCode not only prepares candidates for technical interviews but also assists companies in discovering top-notch technical talent. By sponsoring contests and offering online assessments and training, we provide a variety of services tailored for businesses. Now supporting 14 widely-used coding languages, LeetCode places developers at the forefront of its mission. Additionally, our robust development tools, such as Playground, empower users to test, debug, and create their own projects directly online, making the learning experience even more dynamic. With such extensive resources and community involvement, your journey in programming has never been more promising.

Apache Hive is a data warehouse solution that enables the efficient reading, writing, and management of substantial datasets stored across distributed systems using SQL. It allows users to apply structure to pre-existing data in storage. To facilitate user access, it comes equipped with a command line interface and a JDBC driver. As an open-source initiative, Apache Hive is maintained by dedicated volunteers at the Apache Software Foundation. Initially part of the Apache® Hadoop® ecosystem, it has since evolved into an independent top-level project. We invite you to explore the project further and share your knowledge to enhance its development. Users typically implement traditional SQL queries through the MapReduce Java API, which can complicate the execution of SQL applications on distributed data. However, Hive simplifies this process by offering a SQL abstraction that allows for the integration of SQL-like queries, known as HiveQL, into the underlying Java framework, eliminating the need to delve into the complexities of the low-level Java API. This makes working with large datasets more accessible and efficient for developers.

Apache Kafka® is a robust, open-source platform designed for distributed streaming. It can scale production environments to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data with hundreds of thousands of partitions. The system allows for elastic growth and reduction of both storage and processing capabilities. Furthermore, it enables efficient cluster expansion across availability zones or facilitates the interconnection of distinct clusters across various geographic locations. Users can process event streams through features such as joins, aggregations, filters, transformations, and more, all while utilizing event-time and exactly-once processing guarantees. Kafka's built-in Connect interface seamlessly integrates with a wide range of event sources and sinks, including Postgres, JMS, Elasticsearch, AWS S3, among others. Additionally, developers can read, write, and manipulate event streams using a diverse selection of programming languages, enhancing the platform's versatility and accessibility. This extensive support for various integrations and programming environments makes Kafka a powerful tool for modern data architectures.

Trino is a remarkably fast query engine designed to operate at exceptional speeds. It serves as a high-performance, distributed SQL query engine tailored for big data analytics, enabling users to delve into their vast data environments. Constructed for optimal efficiency, Trino excels in low-latency analytics and is extensively utilized by some of the largest enterprises globally to perform queries on exabyte-scale data lakes and enormous data warehouses. It accommodates a variety of scenarios, including interactive ad-hoc analytics, extensive batch queries spanning several hours, and high-throughput applications that require rapid sub-second query responses. Trino adheres to ANSI SQL standards, making it compatible with popular business intelligence tools like R, Tableau, Power BI, and Superset. Moreover, it allows direct querying of data from various sources such as Hadoop, S3, Cassandra, and MySQL, eliminating the need for cumbersome, time-consuming, and error-prone data copying processes. This capability empowers users to access and analyze data from multiple systems seamlessly within a single query. Such versatility makes Trino a powerful asset in today's data-driven landscape.

Iceberg is an advanced format designed for managing extensive analytical tables efficiently. It combines the dependability and ease of SQL tables with the capabilities required for big data, enabling multiple engines such as Spark, Trino, Flink, Presto, Hive, and Impala to access and manipulate the same tables concurrently without issues. The format allows for versatile SQL operations to incorporate new data, modify existing records, and execute precise deletions. Additionally, Iceberg can optimize read performance by eagerly rewriting data files or utilize delete deltas to facilitate quicker updates. It also streamlines the complex and often error-prone process of generating partition values for table rows while automatically bypassing unnecessary partitions and files. Fast queries do not require extra filtering, and the structure of the table can be adjusted dynamically as data and query patterns evolve, ensuring efficiency and adaptability in data management. This adaptability makes Iceberg an essential tool in modern data workflows.

Leverage your data, regardless of its location, with an open and hybrid data lakehouse designed specifically for AI and analytics. Seamlessly integrate data from various sources and formats, all accessible through a unified entry point featuring a shared metadata layer. Enhance both cost efficiency and performance by aligning specific workloads with the most suitable query engines. Accelerate the discovery of generative AI insights with integrated natural-language semantic search, eliminating the need for SQL queries. Ensure that your AI applications are built on trusted data to enhance their relevance and accuracy. Maximize the potential of all your data, wherever it exists. Combining the rapidity of a data warehouse with the adaptability of a data lake, watsonx.data is engineered to facilitate the expansion of AI and analytics capabilities throughout your organization. Select the most appropriate engines tailored to your workloads to optimize your strategy. Enjoy the flexibility to manage expenses, performance, and features with access to an array of open engines, such as Presto, Presto C++, Spark Milvus, and many others, ensuring that your tools align perfectly with your data needs. This comprehensive approach allows for innovative solutions that can drive your business forward.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

PostgreSQL stands out as a highly capable, open-source object-relational database system that has been actively developed for more than three decades, earning a solid reputation for its reliability, extensive features, and impressive performance. Comprehensive resources for installation and usage are readily available in the official documentation, which serves as an invaluable guide for both new and experienced users. Additionally, the open-source community fosters numerous forums and platforms where individuals can learn about PostgreSQL, understand its functionalities, and explore job opportunities related to it. Engaging with this community can enhance your knowledge and connection to the PostgreSQL ecosystem. Recently, the PostgreSQL Global Development Group announced updates for all supported versions, including 15.1, 14.6, 13.9, 12.13, 11.18, and 10.23, which address 25 reported bugs from the past few months. Notably, this marks the final release for PostgreSQL 10, meaning that it will no longer receive any security patches or bug fixes going forward. Therefore, if you are currently utilizing PostgreSQL 10 in your production environment, it is highly recommended that you plan to upgrade to a more recent version to ensure continued support and security. Upgrading will not only help maintain the integrity of your data but also allow you to take advantage of the latest features and improvements introduced in newer releases.

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Aggregate all your data seamlessly using Enterprise plugins such as Splunk, ServiceNow, Datadog, and others. The integrated collaboration tools enable teams to engage efficiently from a unified dashboard. With enhanced security and compliance features, you can rest assured that your data remains protected at all times. Gain insights from experts in Prometheus, Graphite, and Grafana, along with dedicated support teams ready to assist. While other providers may promote a "one-size-fits-all" database solution, Grafana Labs adopts a different philosophy: we focus on empowering your observability rather than controlling it. Grafana Enterprise offers access to a range of enterprise plugins that seamlessly integrate your current data sources into Grafana. This innovative approach allows you to maximize the potential of your sophisticated and costly monitoring systems by presenting all your data in a more intuitive and impactful manner. Ultimately, our goal is to enhance your data visualization experience, making it simpler and more effective for your organization.

Introducing our innovative Contactless Dining Solution, which comes with a $0 monthly fee. As the leading provider of contactless dining technology globally, we have over 100 million active users each month and have successfully shipped more than 300,000 systems. Our solution allows restaurants to deliver a seamless, end-to-end contactless dining experience, enabling guests to browse the full menu, place orders, and pay at their table—all without any physical interaction. By signing up today, you can transition to a completely contactless service in just three days, and enjoy the benefits of no recurring fees (though standard payment processing charges do apply), without needing to modify your current POS system. While our solution is available worldwide, supplies are limited due to high demand, so it's essential to reserve your spot promptly. Join the growing number of over 100 million monthly users already benefiting from Presto, as we continue to dominate the contactless dining market in both the U.S. and Europe. Experience the future of dining and enhance your restaurant's service by embracing this technology today!

SQL is a specialized programming language designed specifically for the purpose of retrieving, organizing, and modifying data within relational databases and the systems that manage them. Its use is essential for effective database management and interaction.

The Unity Catalog from Databricks stands out as the sole comprehensive and open governance framework tailored for data and artificial intelligence, integrated within the Databricks Data Intelligence Platform. This innovative solution enables organizations to effortlessly manage structured and unstructured data in various formats, in addition to machine learning models, notebooks, dashboards, and files on any cloud or platform. Data scientists, analysts, and engineers can securely navigate, access, and collaborate on reliable data and AI resources across diverse environments, harnessing AI capabilities to enhance efficiency and realize the full potential of the lakehouse architecture. By adopting this cohesive and open governance strategy, organizations can foster interoperability and expedite their data and AI projects, all while making regulatory compliance easier to achieve. Furthermore, users can quickly identify and categorize both structured and unstructured data, including machine learning models, notebooks, dashboards, and files, across all cloud platforms, ensuring a streamlined governance experience. This comprehensive approach not only simplifies data management but also encourages a collaborative culture among teams.