Best Big Data Software for cnvrg.io

Find and compare the best Big Data software for cnvrg.io in 2025

Use the comparison tool below to compare the top Big Data software for cnvrg.io on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Sisense Reviews
    Integrate analytics into any workflow or application to make crucial decisions - confidently. Analytics can be integrated into your everyday workflows and applications to help you make better and faster decisions for your business and customers. To make analytics easy and intuitive, integrate customized analytics into your products and applications. The AI-driven predictive analytics platform is designed to increase product adoption, retention, and engagement. Sisense, a top-rated Business Intelligence (BI), reporting software, allows you to prepare, analyze, and examine data from multiple sources. Sisense is trusted by industry-leading companies like NASDAQ, Phillips and Airbus. It offers an end to end, agile BI platform that enables businesses to make better, faster data-driven business decisions. Sisense has an open, single-stack architecture that enables machine learning, best-in class analytics engines, and delivers insights beyond the dashboard.
  • 2
    Google Cloud Platform Reviews
    Top Pick

    Google Cloud Platform

    Google

    Free ($300 in free credits)
    25 Ratings
    Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.
  • 3
    Google Cloud BigQuery Reviews
    ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys
  • 4
    Apache Spark Reviews

    Apache Spark

    Apache Software Foundation

    Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.
  • Previous
  • You're on page 1
  • Next