Best Data Management Software for Fluentd

Find and compare the best Data Management software for Fluentd in 2024

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

  • 1
    Google Cloud Platform Reviews
    Top Pick

    Google Cloud Platform

    Google

    Free ($300 in free credits)
    55,132 Ratings
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    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.
  • 2
    groundcover Reviews

    groundcover

    groundcover

    $20/month/node
    32 Ratings
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    Cloud-based solution for observability that helps businesses manage and track workload and performance through a single dashboard. Monitor all the services you run on your cloud without compromising cost, granularity or scale. Groundcover is a cloud-native APM solution that makes observability easy so you can focus on creating world-class products. Groundcover's proprietary sensor unlocks unprecedented granularity for all your applications. This eliminates the need for costly changes in code and development cycles, ensuring monitoring continuity.
  • 3
    Elasticsearch Reviews
    Elastic is a search company. Elasticsearch, Kibana Beats, Logstash, and Elasticsearch are the founders of the ElasticStack. These SaaS offerings allow data to be used in real-time and at scale for analytics, security, search, logging, security, and search. Elastic has over 100,000 members in 45 countries. Elastic's products have been downloaded more than 400 million times since their initial release. Today, thousands of organizations including Cisco, eBay and Dell, Goldman Sachs and Groupon, HP and Microsoft, as well as Netflix, Uber, Verizon and Yelp use Elastic Stack and Elastic Cloud to power mission critical systems that generate new revenue opportunities and huge cost savings. Elastic is headquartered in Amsterdam, The Netherlands and Mountain View, California. It has more than 1,000 employees in over 35 countries.
  • 4
    MongoDB Reviews
    Top Pick
    MongoDB is a distributed database that supports document-based applications and is designed for modern application developers. No other database is more productive. Our flexible document data model allows you to ship and iterate faster and provides a unified query interface that can be used for any purpose. No matter if it's your first customer, or 20 million users worldwide, you can meet your performance SLAs in every environment. You can easily ensure high availability, data integrity, and meet compliance standards for mission-critical workloads. A comprehensive suite of cloud database services that allows you to address a wide range of use cases, including transactional, analytical, search, and data visualizations. Secure mobile apps can be launched with native, edge to-cloud sync and automatic conflicts resolution. MongoDB can be run anywhere, from your laptop to the data center.
  • 5
    Coralogix Reviews
    Coralogix is the most popular stateful streaming platform, providing engineering teams with real-time insight and long-term trend analysis without relying on storage or indexing. To manage, monitor, alert, and manage your applications, you can import data from any source. Coralogix automatically narrows the data from millions of events to common patterns, allowing for faster troubleshooting and deeper insights. Machine learning algorithms constantly monitor data patterns and flows among system components and trigger dynamic alarms to let you know when a pattern is out of the norm without the need for static thresholds or pre-configurations. Connect any data in any format and view your insights anywhere, including our purpose-built UI and Kibana, Grafana as well as SQL clients and Tableau. You can also use our CLI and full API support. Coralogix has successfully completed the relevant privacy and security compliances by BDO, including SOC 2, PCI and GDPR.
  • 6
    Prometheus Reviews
    Open-source monitoring solutions are able to power your alerting and metrics. Prometheus stores all data in time series. These are streams of timestamped value belonging to the same metric with the same labeled dimensions. Prometheus can also generate temporary derived times series as a result of queries. Prometheus offers a functional query language called PromQL, which allows the user to select and aggregate time series data real-time. The expression result can be displayed as a graph or tabular data in Prometheus’s expression browser. External systems can also consume the HTTP API. Prometheus can be configured using command-line flags or a configuration file. The command-line flags can be used to configure immutable system parameters such as storage locations and the amount of data to be kept on disk and in memory. . Download: https://sourceforge.net/projects/prometheus.mirror/
  • 7
    MaxCompute Reviews
    MaxCompute, formerly known as ODPS, is a multi-tenant, general-purpose data processing platform that can be used for large-scale data warehousing. MaxCompute supports a variety of data importing options and distributed computing models. This allows users to query large datasets efficiently, reduce production costs, and ensure data safety. Supports EB-level data storage. Supports SQL, MapReduce and Graph computational models as well as Message Passing Interface (MPI), iterative algorithms. This cloud is more efficient than an enterprise private cloud and offers storage and computing services that are up to 20% to 30% cheaper. Stable offline analysis services that last more than seven years. Also, multi-level sandbox protection is possible. Monitoring and monitoring are possible. MaxCompute uses tunnels for data transmission. Tunnels can be scaled and used to import and export PB-level data daily. Multiple tunnels allow you to import all data and history data.
  • 8
    DataWorks Reviews
    Alibaba Cloud launched DataWorks, a Big Data platform product. It offers Big Data development, data permission management and offline job scheduling. DataWorks is easy to use and does not require any special cluster setup or management. To create a workflow, drag and drop nodes. Online editing and debugging of code is possible. You can also ask other developers to join your project. Data integration, MaxCompute SQL and MaxCompute MS, machine learning, shell tasks, and MaxCompute MR are supported. To prevent service interruptions, task monitoring is supported. It sends alarms when errors are detected. It can run millions of tasks simultaneously and supports hourly, daily and weekly schedules. DataWorks is the best platform to build big data warehouses. It also offers comprehensive data warehousing and support services. DataWorks offers a complete solution for data aggregation and processing, as well as data governance and data services.
  • 9
    Hadoop Reviews

    Hadoop

    Apache Software Foundation

    Apache Hadoop is a software library that allows distributed processing of large data sets across multiple computers. It uses simple programming models. It can scale from one server to thousands of machines and offer local computations and storage. Instead of relying on hardware to provide high-availability, it is designed to detect and manage failures at the application layer. This allows for highly-available services on top of a cluster computers that may be susceptible to failures.
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