Best Data Management Software for KubeSphere

Find and compare the best Data Management software for KubeSphere in 2025

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

  • 1
    MySQL Reviews
    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.
  • 2
    DigitalOcean Reviews

    DigitalOcean

    DigitalOcean

    $5 per month
    4 Ratings
    The easiest cloud platform for developers and teams. DigitalOcean makes it easy to deploy, manage, and scale cloud apps faster and more efficiently. DigitalOcean makes it easy to manage infrastructure for businesses and teams, no matter how many virtual machines you have. DigitalOcean App Platform: Create, deploy, scale and scale apps quickly with a fully managed solution. We will manage the infrastructure, dependencies, and app runtimes so you can quickly push code to production. You can quickly build, deploy, manage, scale, and scale apps using a simple, intuitive, visually rich experience. Apps are automatically secured We manage, renew, and create SSL certificates for you. We also protect your apps against DDoS attacks. We help you focus on the important things: creating amazing apps. We can manage infrastructure, databases, operating systems, applications, runtimes, and other dependencies.
  • 3
    Redis Reviews
    Redis Labs is the home of Redis. Redis Enterprise is the best Redis version. Redis Enterprise is more than a cache. Redis Enterprise can be free in the cloud with NoSQL and data caching using the fastest in-memory database. Redis can be scaled, enterprise-grade resilience, massive scaling, ease of administration, and operational simplicity. Redis in the Cloud is a favorite of DevOps. Developers have access to enhanced data structures and a variety modules. This allows them to innovate faster and has a faster time-to-market. CIOs love the security and expert support of Redis, which provides 99.999% uptime. Use relational databases for active-active, geodistribution, conflict distribution, reads/writes in multiple regions to the same data set. Redis Enterprise offers flexible deployment options. Redis Labs is the home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.
  • 4
    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.
  • 5
    Apache Kafka Reviews

    Apache Kafka

    The Apache Software Foundation

    1 Rating
    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.
  • 6
    Prometheus Reviews
    Enhance your metrics and alerting capabilities using a top-tier open-source monitoring tool. Prometheus inherently organizes all data as time series, which consist of sequences of timestamped values associated with the same metric and a specific set of labeled dimensions. In addition to the stored time series, Prometheus has the capability to create temporary derived time series based on query outcomes. The tool features a powerful query language known as PromQL (Prometheus Query Language), allowing users to select and aggregate time series data in real time. The output from an expression can be displayed as a graph, viewed in tabular format through Prometheus’s expression browser, or accessed by external systems through the HTTP API. Configuration of Prometheus is achieved through a combination of command-line flags and a configuration file, where the flags are used to set immutable system parameters like storage locations and retention limits for both disk and memory. This dual method of configuration ensures a flexible and tailored monitoring setup that can adapt to various user needs. For those interested in exploring this robust tool, further details can be found at: https://sourceforge.net/projects/prometheus.mirror/
  • 7
    Fluentd Reviews

    Fluentd

    Fluentd Project

    Establishing a cohesive logging framework is essential for ensuring that log data is both accessible and functional. Unfortunately, many current solutions are inadequate; traditional tools do not cater to the demands of modern cloud APIs and microservices, and they are not evolving at a sufficient pace. Fluentd, developed by Treasure Data, effectively tackles the issues associated with creating a unified logging framework through its modular design, extensible plugin system, and performance-enhanced engine. Beyond these capabilities, Fluentd Enterprise also fulfills the needs of large organizations by providing features such as Trusted Packaging, robust security measures, Certified Enterprise Connectors, comprehensive management and monitoring tools, as well as SLA-based support and consulting services tailored for enterprise clients. This combination of features makes Fluentd a compelling choice for businesses looking to enhance their logging infrastructure.
  • 8
    PostgreSQL Reviews

    PostgreSQL

    PostgreSQL Global Development Group

    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.
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