What Integrates with Spark?

Find out what Spark integrations exist in 2025. Learn what software and services currently integrate with Spark, and sort them by reviews, cost, features, and more. Below is a list of products that Spark currently integrates with:

  • 1
    Sematext Cloud Reviews
    Top Pick
    Sematext Cloud provides all-in-one observability solutions for modern software-based businesses. It provides key insights into both front-end and back-end performance. Sematext includes infrastructure, synthetic monitoring, transaction tracking, log management, and real user & synthetic monitoring. Sematext provides full-stack visibility for businesses by quickly and easily exposing key performance issues through a single Cloud solution or On-Premise.
  • 2
    Knowi Reviews
    Business Intelligence, AI & NLP are available to anyone who wants to make data-driven business decisions. Knowi instantly transforms data into insights and data-driven actions. No ETL. No ODBC drivers. Simply connect your datasources to start building queries. It's that simple. In a matter of minutes, you can create blended datasets by joining data sources from NoSQL and SQL, REST API, and even file-based sources. Click. Done. We have combined the power and natural language queries of AI to create a new self-service experience in BI that makes it easier to find and reveal new insights. The data we have today is large and scattered. A business intelligence solution is required to instantly connect to modern data. Knowi is the only full-stack analytics platform that integrates natively to all popular NoSQL data sources, as well as relational or Cloud APIs.
  • 3
    CData API Server Reviews
    The CData API Server makes it easy to create and deploy data-driven APIs. API Server allows users to create APIs that provide back-ends to internal applications, enable mobile development projects, expose data and deploy microservices of enterprise-class quality. The API Server is an application that comes with everything you need to create, manage, secure, and run APIs. It does not require any custom development. It allows you to create and distribute self-contained API endpoints on-premise and to the cloud. These endpoints can connect to any database or application and translate REST, JSON and OData API calls into your IT resources. API server includes API-critical features such as access-control, data security monitoring and management. It is a powerful tool that can modernize your back-end infrastructure. Download a 30-day free trial of CData API Server or learn more at: https://www.cdata.com/apiserver/
  • 4
    Datameer Reviews
    Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.
  • 5
    Algonomy Reviews
    Algonomy's real-time Customer Data Platform (CDP) empowers marketers to deliver tailored customer experiences consistently and instantly. By consolidating customer identities from both online and offline sources, it facilitates immediate audience activation for a comprehensive perspective. Specifically designed for the retail sector, it can monitor customer actions using over 1,200 predefined metrics and attributes. The platform leverages machine learning algorithms to generate micro-segments, provide in-depth insights, and identify marketing opportunities at every stage of the customer journey. This innovative approach ensures that businesses can engage their customers effectively and adapt to their evolving needs in real-time.
  • 6
    HugeGraph Reviews
    HugeGraph is a high-performance and scalable graph database capable of managing billions of vertices and edges efficiently due to its robust OLTP capabilities. This database allows for seamless storage and querying, making it an excellent choice for complex data relationships. It adheres to the Apache TinkerPop 3 framework, enabling users to execute sophisticated graph queries using Gremlin, a versatile graph traversal language. Key features include Schema Metadata Management, which encompasses VertexLabel, EdgeLabel, PropertyKey, and IndexLabel, providing comprehensive control over graph structures. Additionally, it supports Multi-type Indexes that facilitate exact queries, range queries, and complex conditional queries. The platform also boasts a Plug-in Backend Store Driver Framework that currently supports various databases like RocksDB, Cassandra, ScyllaDB, HBase, and MySQL, while also allowing for easy integration of additional backend drivers as necessary. Moreover, HugeGraph integrates smoothly with Hadoop and Spark, enhancing its data processing capabilities. By drawing on the storage structure of Titan and the schema definitions from DataStax, HugeGraph offers a solid foundation for effective graph database management. This combination of features positions HugeGraph as a versatile and powerful solution for handling complex graph data scenarios.
  • 7
    BDB Platform Reviews
    BDB is an advanced platform for data analytics and business intelligence that excels in extracting valuable insights from your data. It can be implemented both in cloud environments and on-premises. With a unique microservices architecture, it incorporates components for Data Preparation, Predictive Analytics, Pipelines, and Dashboard design, enabling tailored solutions and scalable analytics across various sectors. Thanks to its robust NLP-driven search functionality, users can harness the potential of data seamlessly across desktops, tablets, and mobile devices. BDB offers numerous integrated data connectors, allowing it to interface with a wide array of popular data sources, applications, third-party APIs, IoT devices, and social media platforms in real-time. It facilitates connections to relational databases, big data systems, FTP/SFTP servers, flat files, and web services, effectively managing structured, semi-structured, and unstructured data. Embark on your path to cutting-edge analytics today, and discover the transformative power of BDB for your organization.
  • 8
    dashDB Local Reviews
    DashDB Local, the latest addition to IBM's dashDB suite, enhances the company's hybrid data warehouse strategy by equipping organizations with a highly adaptable architecture that reduces the cost of analytics in the rapidly evolving landscape of big data and cloud computing. This is achievable thanks to a unified analytics engine that supports various deployment methods in both private and public cloud environments, allowing for seamless migration and optimization of analytics workloads. Now available for those who prefer deploying in a hosted private cloud or an on-premises private cloud via a software-defined infrastructure, dashDB Local presents a versatile choice. From an IT perspective, it streamlines deployment and management through the use of container technology, ensuring elastic scalability and straightforward maintenance. On the user side, dashDB Local accelerates the data acquisition process, applies tailored analytics for specific scenarios, and effectively turns insights into actionable operations, ultimately enhancing overall productivity. This comprehensive approach empowers organizations to harness their data more effectively than ever before.
  • 9
    Apache Atlas Reviews

    Apache Atlas

    Apache Software Foundation

    Atlas serves as a versatile and scalable suite of essential governance services, empowering organizations to efficiently comply with regulations within the Hadoop ecosystem while facilitating integration across the enterprise's data landscape. Apache Atlas offers comprehensive metadata management and governance tools that assist businesses in creating a detailed catalog of their data assets, effectively classifying and managing these assets, and fostering collaboration among data scientists, analysts, and governance teams. It comes equipped with pre-defined types for a variety of both Hadoop and non-Hadoop metadata, alongside the capability to establish new metadata types tailored to specific needs. These types can incorporate primitive attributes, complex attributes, and object references, and they can also inherit characteristics from other types. Entities, which are instances of these types, encapsulate the specifics of metadata objects and their interconnections. Additionally, REST APIs enable seamless interaction with types and instances, promoting easier integration and enhancing overall functionality. This robust framework not only streamlines governance processes but also supports a culture of data-driven collaboration across the organization.
  • 10
    Mage Static Data Masking Reviews
    Mage™ offers comprehensive Static Data Masking (SDM) and Test Data Management (TDM) functionalities that are fully compatible with Imperva’s Data Security Fabric (DSF), ensuring robust safeguarding of sensitive or regulated information. This integration occurs smoothly within an organization’s current IT infrastructure and aligns with existing application development, testing, and data processes, all without necessitating any alterations to the existing architectural setup. As a result, organizations can enhance their data security while maintaining operational efficiency.
  • 11
    Mage Dynamic Data Masking Reviews
    The Mage™ Dynamic Data Masking module, part of the Mage data security platform, has been thoughtfully crafted with a focus on the needs of end customers. Developed in collaboration with clients, Mage™ Dynamic Data Masking effectively addresses their unique requirements and challenges. Consequently, this solution has advanced to accommodate virtually every potential use case that enterprises might encounter. Unlike many competing products that often stem from acquisitions or cater to niche scenarios, Mage™ Dynamic Data Masking is designed to provide comprehensive protection for sensitive data accessed by application and database users in production environments. Additionally, it integrates effortlessly into an organization’s existing IT infrastructure, eliminating the need for any substantial architectural modifications, thus ensuring a smoother transition for businesses implementing this solution. This strategic approach reflects a commitment to enhancing data security while prioritizing user experience and operational efficiency.
  • Previous
  • You're on page 1
  • Next