Best Cluster Management Software for Apache Spark
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Compare the Top Cluster Management Software that integrates with Apache Spark as of November 2025
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This a list of Cluster Management software that integrates with Apache Spark. Use the filters on the left to add additional filters for products that have integrations with Apache Spark. View the products that work with Apache Spark in the table below.
What is Cluster Management Software for Apache Spark?
Cluster management software is specialized software designed to manage and orchestrate groups of interconnected computers, known as clusters, that work together to perform complex tasks. It provides a centralized interface for deploying, monitoring, scaling, and maintaining applications and workloads across multiple nodes. The software ensures resource allocation, load balancing, and fault tolerance to maximize efficiency and reliability. It is commonly used in high-performance computing, data centers, and cloud environments to streamline operations and optimize infrastructure usage. By automating tasks and providing real-time insights, cluster management software enhances operational efficiency and simplifies the complexities of managing distributed systems. Compare and read user reviews of the best Cluster Management software for Apache Spark currently available using the table below. This list is updated regularly.
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Kubernetes
Kubernetes
Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.Starting Price: Free -
2
Apache Mesos
Apache Software Foundation
Mesos is built using the same principles as the Linux kernel, only at a different level of abstraction. The Mesos kernel runs on every machine and provides applications (e.g., Hadoop, Spark, Kafka, Elasticsearch) with API’s for resource management and scheduling across entire datacenter and cloud environments. Native support for launching containers with Docker and AppC images.Support for running cloud native and legacy applications in the same cluster with pluggable scheduling policies. HTTP APIs for developing new distributed applications, for operating the cluster, and for monitoring. Built-in Web UI for viewing cluster state and navigating container sandboxes. -
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Sync
Sync Computing
Sync Computing offers Gradient, an AI-powered compute optimization engine designed to enhance data infrastructure efficiency. By leveraging advanced machine learning algorithms developed at MIT, Gradient provides automated optimization for organizations running data workloads on cloud-based CPUs or GPUs. Users can achieve up to 50% cost savings on their Databricks compute expenses while consistently meeting runtime service level agreements (SLAs). Gradient's continuous monitoring and fine-tuning capabilities ensure optimal performance across complex data pipelines, adapting seamlessly to varying data sizes and workload patterns. The platform integrates with existing data tools and supports multiple cloud providers, offering a comprehensive solution for managing and optimizing data infrastructure.
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