Apache Atlas Integrations

AWS is the leading provider of cloud computing, delivering over 200 fully featured services to organizations worldwide. Its offerings cover everything from infrastructure—such as compute, storage, and networking—to advanced technologies like artificial intelligence, machine learning, and agentic AI. Businesses use AWS to modernize legacy systems, run high-performance workloads, and build scalable, secure applications. Core services like Amazon EC2, Amazon S3, and Amazon DynamoDB provide foundational capabilities, while advanced solutions like SageMaker and AWS Transform enable AI-driven transformation. The platform is supported by a global infrastructure that includes 38 regions, 120 availability zones, and 400+ edge locations, ensuring low latency and high reliability. AWS integrates with leading enterprise tools, developer SDKs, and partner ecosystems, giving teams the flexibility to adopt cloud at their own pace. Its training and certification programs help individuals and companies grow cloud expertise with industry-recognized credentials. With its unmatched breadth, depth, and proven track record, AWS empowers organizations to innovate and compete in the digital-first economy.

Hackolade Studio is a comprehensive data modeling platform built for today’s complex and hybrid data ecosystems. Originally developed to address the lack of visual design tools for NoSQL databases, Hackolade has evolved into a multi-model solution that supports the broadest range of data technologies in the industry. The platform enables agile, iterative schema design and governance for both structured and semi-structured data, making it ideal for organizations working across traditional RDBMS, modern data warehouses, NoSQL stores, and streaming systems. Hackolade supports technologies such as Oracle, PostgreSQL, BigQuery, Databricks, Redshift, Snowflake, MongoDB, Cassandra, DynamoDB, Neo4j, Kafka (with Confluent Schema Registry), OpenAPI, GraphQL, and more. Beyond databases, Hackolade Studio offers robust capabilities for API modeling, supporting OpenAPI (Swagger) and GraphQL, as well as native modeling for data exchange formats like JSON Schema, Avro, Protobuf, Parquet, and YAML. It also integrates with metadata and data governance platforms like Unity Catalog and Collibra, making it a powerful enabler for organizations focused on data quality, lineage, and compliance. Key features include reverse and forward engineering, schema versioning, data type mapping, and team collaboration tools. Whether you're building data products, managing data contracts, or migrating between systems, Hackolade Studio provides a unified interface for modeling, documenting, and evolving your schemas. Hackolade is trusted by enterprises across finance, retail, healthcare, and telecom to align data architecture with real-world delivery. It’s an essential tool for teams implementing data mesh, data fabric, microservices, or API-first strategies.

Hue delivers an exceptional querying experience through its advanced autocomplete features and sophisticated query editor components. Users can seamlessly navigate tables and storage browsers, utilizing their existing knowledge of data catalogs. This functionality assists in locating the right data within extensive databases while also enabling self-documentation. Furthermore, the platform supports users in crafting SQL queries and provides rich previews for links, allowing for direct sharing in Slack from the editor. There is a variety of applications available, each tailored to specific querying needs, and data sources can be initially explored through the intuitive browsers. The editor excels particularly in SQL queries, equipped with intelligent autocomplete, risk alerts, and self-service troubleshooting capabilities. While dashboards are designed to visualize indexed data, they also possess the ability to query SQL databases effectively. Users can now search for specific cell values in tables, with results highlighted for easy identification. Additionally, Hue's SQL editing capabilities are considered among the finest globally, ensuring a streamlined and efficient experience for all users. This combination of features makes Hue a powerful tool for data exploration and management.

Develop training datasets for computer vision models using our comprehensive management solution. We are convinced that the quality of data labeling plays a crucial role in crafting successful deep learning models. Our mission is to establish ourselves as the foremost data labeling platform in the industry, enabling businesses to fully leverage the potential of AI technology. Organize your media assets into distinct categories for better management. Highlight specific items of interest using one or multiple bounding boxes to enhance detection accuracy. Utilize bounding boxes with added precision for more detailed annotations. Provide accurate measurements of width, depth, and height for various objects. Classify every pixel in an image for fine-grained analysis. Identify and mark individual points to capture specific details within images. Annotate straight lines to assist in geometric assessments. Measure critical attributes like yaw, pitch, and roll for items of interest. Keep track of timestamps in both video and audio content for synchronization purposes. Additionally, annotate freeform lines in images to capture more complex shapes and designs, enhancing the depth of your data labeling efforts.

Beats serves as a free and accessible platform designed specifically for single-purpose data shippers that transport data from numerous machines and systems to Logstash or Elasticsearch. These open-source data shippers are installed as agents on your servers, enabling the seamless transfer of operational data to Elasticsearch. Elastic offers Beats to facilitate the collection of data and event logs efficiently. Data can be directed to Elasticsearch or routed through Logstash, allowing for additional processing and enhancement before visualization in Kibana. If you're eager to start monitoring infrastructure metrics and centralizing log analytics swiftly, the Metrics app and Logs app in Kibana are excellent resources to explore. For comprehensive guidance, refer to Analyze metrics and Monitor logs. Filebeat simplifies the process of collecting data from various sources, including security devices, cloud environments, containers, and hosts, by providing a lightweight solution to forward and centralize logs and files. This flexibility ensures that you can maintain an organized and efficient data pipeline regardless of the complexity of your infrastructure.

Digital contracts seamlessly integrated with your CRM and marketing tools streamline your sales and marketing efforts through a single login, eliminating the hassle of juggling multiple platforms. Tailored specifically for the real estate sector, Spark empowers your team to manage the complete sales cycle, from inventory oversight to contract creation. Every developer has their own criteria for evaluating contacts, and team structures vary widely; thus, Spark allows for customization to fit your unique workflow without causing disruptions. No matter whether you deal in condos, townhomes, master-planned communities, single-family homes, or apartments, Spark offers the comprehensive platform necessary for selling, marketing, closing, and reporting on your full range of new development projects. Our commitment begins with understanding your goals, ensuring the platform is adapted to meet your team's preferences and the specific requirements of your region. The consultative process initiates with the development of an onboarding and training strategy that engages your entire team, fostering a collaborative environment for success. This personalized approach ensures that Spark not only meets your current needs but also evolves alongside your business as it grows.

The Apache Hadoop software library serves as a framework for the distributed processing of extensive data sets across computer clusters, utilizing straightforward programming models. It is built to scale from individual servers to thousands of machines, each providing local computation and storage capabilities. Instead of depending on hardware for high availability, the library is engineered to identify and manage failures within the application layer, ensuring that a highly available service can run on a cluster of machines that may be susceptible to disruptions. Numerous companies and organizations leverage Hadoop for both research initiatives and production environments. Users are invited to join the Hadoop PoweredBy wiki page to showcase their usage. The latest version, Apache Hadoop 3.3.4, introduces several notable improvements compared to the earlier major release, hadoop-3.2, enhancing its overall performance and functionality. This continuous evolution of Hadoop reflects the growing need for efficient data processing solutions in today's data-driven landscape.

Azure Data Lake offers a comprehensive set of features designed to facilitate the storage of data in any form, size, and speed for developers, data scientists, and analysts alike, enabling a wide range of processing and analytics across various platforms and programming languages. By simplifying the ingestion and storage of data, it accelerates the process of launching batch, streaming, and interactive analytics. Additionally, Azure Data Lake is compatible with existing IT frameworks for identity, management, and security, which streamlines data management and governance. Its seamless integration with operational stores and data warehouses allows for the extension of current data applications without disruption. Leveraging insights gained from working with enterprise clients and managing some of the world's largest processing and analytics tasks for services such as Office 365, Xbox Live, Azure, Windows, Bing, and Skype, Azure Data Lake addresses many of the scalability and productivity hurdles that hinder your ability to fully utilize data. Ultimately, it empowers organizations to harness their data's potential more effectively and efficiently than ever before.

JanusGraph stands out as a highly scalable graph database designed for efficiently storing and querying extensive graphs that can comprise hundreds of billions of vertices and edges, all managed across a cluster of multiple machines. This project, which operates under The Linux Foundation, boasts contributions from notable organizations such as Expero, Google, GRAKN.AI, Hortonworks, IBM, and Amazon. It offers both elastic and linear scalability to accommodate an expanding data set and user community. Key features include robust data distribution and replication methods to enhance performance and ensure fault tolerance. Additionally, JanusGraph supports multi-datacenter high availability and provides hot backups for data security. All these capabilities are available without any associated costs, eliminating the necessity for purchasing commercial licenses, as it is entirely open source and governed by the Apache 2 license. Furthermore, JanusGraph functions as a transactional database capable of handling thousands of simultaneous users performing complex graph traversals in real time. It ensures support for both ACID properties and eventual consistency, catering to various operational needs. Beyond online transactional processing (OLTP), JanusGraph also facilitates global graph analytics (OLAP) through its integration with Apache Spark, making it a versatile tool for data analysis and visualization. This combination of features makes JanusGraph a powerful choice for organizations looking to leverage graph data effectively.

The Occubee platform seamlessly transforms vast quantities of receipt information, encompassing thousands of products along with numerous retail-specific metrics, into actionable sales and demand predictions. At the retail level, Occubee delivers precise sales forecasts for each product and initiates restocking requests. In warehouse settings, it enhances product availability and capital allocation while also generating supplier orders. Furthermore, at the corporate office, Occubee offers continuous oversight of sales activities, issuing alerts for any anomalies and producing comprehensive reports. The innovative technologies employed for data gathering and processing facilitate the automation of crucial business operations within the retail sector. By addressing the evolving requirements of contemporary retail, Occubee aligns perfectly with global megatrends that emphasize data utilization in business strategies. This comprehensive approach not only streamlines operations but also empowers retailers to make informed decisions that enhance overall efficiency.