Best Data Lake Solutions for Amazon EKS

x
View:
Open Source Commercial

Compare the Top Data Lake Solutions that integrate with Amazon EKS as of July 2026

Sort By:
Amazon EKS Data Lake Clear Filters

This a list of Data Lake solutions that integrate with Amazon EKS. Use the filters on the left to add additional filters for products that have integrations with Amazon EKS. View the products that work with Amazon EKS in the table below.

What are Data Lake Solutions for Amazon EKS?

Data lake solutions are platforms designed to store and manage large volumes of structured, semi-structured, and unstructured data in its raw form. Unlike traditional databases, data lakes allow businesses to store data in its native format without the need for preprocessing or schema definition upfront. These solutions provide scalability, flexibility, and high-performance capabilities for handling vast amounts of diverse data, including logs, multimedia, social media posts, sensor data, and more. Data lake solutions typically offer tools for data ingestion, storage, management, analytics, and governance, making them essential for big data analytics, machine learning, and real-time data processing. By consolidating data from various sources, data lakes help organizations gain deeper insights and drive data-driven decision-making. Compare and read user reviews of the best Data Lake solutions for Amazon EKS currently available using the table below. This list is updated regularly.

  • 1
    Hydrolix

    Hydrolix

    Hydrolix

    Hydrolix is a streaming data lake that combines decoupled storage, indexed search, and stream processing to deliver real-time query performance at terabyte-scale for a radically lower cost. CFOs love the 4x reduction in data retention costs. Product teams love 4x more data to work with. Spin up resources when you need them and scale to zero when you don’t. Fine-tune resource consumption and performance by workload to control costs. Imagine what you can build when you don’t have to sacrifice data because of budget. Ingest, enrich, and transform log data from multiple sources including Kafka, Kinesis, and HTTP. Return just the data you need, no matter how big your data is. Reduce latency and costs, eliminate timeouts, and brute force queries. Storage is decoupled from ingest and query, allowing each to independently scale to meet performance and budget targets. Hydrolix’s high-density compression (HDX) typically reduces 1TB of stored data to 55GB.
    Starting Price: $2,237 per month
    View Solution
  • Previous
  • You're on page 1
  • Next

Related Categories