Compare the Top Data Lake Solutions for Cloud as of December 2025

What are Data Lake Solutions for Cloud?

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 Cloud currently available using the table below. This list is updated regularly.

  • 1
    Teradata VantageCloud
    Teradata VantageCloud is a cloud-native platform that combines the scalability of a data lake with the performance of a data warehouse. It enables organizations to ingest, store, and analyze structured and semi-structured data across multi-cloud and hybrid environments. VantageCloud supports open data formats and integrates with modern analytics and AI/ML tools, allowing users to extract insights from raw data without complex migrations. Its unified architecture provides governance, security, and real-time access, making it ideal for enterprises seeking a flexible, intelligent data lake foundation for advanced analytics.
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  • 2
    Archon Data Store

    Archon Data Store

    Platform 3 Solutions

    Archon Data Store is a next-generation enterprise data archiving platform designed to help organizations manage rapid data growth, reduce legacy application costs, and meet global compliance standards. Built on a modern Lakehouse architecture, Archon Data Store unifies data lakes and data warehouses to deliver secure, scalable, and analytics-ready archival storage. The platform supports on-premise, cloud, and hybrid deployments with AES-256 encryption, audit trails, metadata governance, and role-based access control. Archon Data Store offers intelligent storage tiering, high-performance querying, and seamless integration with BI tools. It enables efficient application decommissioning, cloud migration, and digital modernization while transforming archived data into a strategic asset. With Archon Data Store, organizations can ensure long-term compliance, optimize storage costs, and unlock AI-driven insights from historical data.
  • 3
    Narrative

    Narrative

    Narrative

    Create new streams of revenue using the data you already collect with your own branded data shop. Narrative is focused on the fundamental principles that make buying and selling data easier, safer, and more strategic. Ensure that the data you access meets your standards, whatever they may be. Know exactly who you’re working with and how the data was collected. Easily access new supply and demand for a more agile and accessible data strategy. Own your data strategy entirely with end-to-end control of inputs and outputs. Our platform simplifies and automates the most time- and labor-intensive aspects of data acquisition, so you can access new data sources in days, not months. With filters, budget controls, and automatic deduplication, you’ll only ever pay for the data you need, and nothing that you don’t.
    Starting Price: $0
  • 4
    Sprinkle

    Sprinkle

    Sprinkle Data

    Businesses today need to adapt faster with ever evolving customer requirements and preferences. Sprinkle helps you manage these expectations with agile analytics platform that meets changing needs with ease. We started Sprinkle with the goal to simplify end to end data analytics for organisations, so that they don’t worry about integrating data from various sources, changing schemas and managing pipelines. We built a platform that empowers everyone in the organisation to browse and dig deeper into the data without any technical background. Our team has worked extensively with data while building analytics systems for companies like Flipkart, Inmobi, and Yahoo. These companies succeed by maintaining dedicated teams of data scientists, business analyst and engineers churning out reports and insights. We realized that most organizations struggle for simple self-serve reporting and data exploration. So we set out to build solution that will help all companies leverage data.
    Starting Price: $499 per month
  • 5
    JFrog ML
    JFrog ML (formerly Qwak) offers an MLOps platform designed to accelerate the development, deployment, and monitoring of machine learning and AI applications at scale. The platform enables organizations to manage the entire lifecycle of machine learning models, from training to deployment, with tools for model versioning, monitoring, and performance tracking. It supports a wide variety of AI models, including generative AI and LLMs (Large Language Models), and provides an intuitive interface for managing prompts, workflows, and feature engineering. JFrog ML helps businesses streamline their ML operations and scale AI applications efficiently, with integrated support for cloud environments.
  • 6
    Openbridge

    Openbridge

    Openbridge

    Uncover insights to supercharge sales growth using code-free, fully-automated data pipelines to data lakes or cloud warehouses. A flexible, standards-based platform to unify sales and marketing data for automating insights and smarter growth. Say goodbye to messy, expensive manual data downloads. Always know what you’ll pay and only pay for what you use. Fuel your tools with quick access to analytics-ready data. As certified developers, we only work with secure, official APIs. Get started quickly with data pipelines from popular sources. Pre-built, pre-transformed, and ready-to-go data pipelines. Unlock data from Amazon Vendor Central, Amazon Seller Central, Instagram Stories, Facebook, Amazon Advertising, Google Ads, and many others. Code-free data ingestion and transformation processes allow teams to realize value from their data quickly and cost-effectively. Data is always securely stored directly in a trusted, customer-owned data destination like Databricks, Amazon Redshift, etc.
    Starting Price: $149 per month
  • 7
    BigLake

    BigLake

    Google

    BigLake is a storage engine that unifies data warehouses and lakes by enabling BigQuery and open-source frameworks like Spark to access data with fine-grained access control. BigLake provides accelerated query performance across multi-cloud storage and open formats such as Apache Iceberg. Store a single copy of data with uniform features across data warehouses & lakes. Fine-grained access control and multi-cloud governance over distributed data. Seamless integration with open-source analytics tools and open data formats. Unlock analytics on distributed data regardless of where and how it’s stored, while choosing the best analytics tools, open source or cloud-native over a single copy of data. Fine-grained access control across open source engines like Apache Spark, Presto, and Trino, and open formats such as Parquet. Performant queries over data lakes powered by BigQuery. Integrates with Dataplex to provide management at scale, including logical data organization.
    Starting Price: $5 per TB
  • 8
    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
  • 9
    Utilihive

    Utilihive

    Greenbird Integration Technology

    Utilihive is a cloud-native big data integration platform, purpose-built for the digital data-driven utility, offered as a managed service (SaaS). Utilihive is the leading Enterprise-iPaaS (iPaaS) that is purpose-built for energy and utility usage scenarios. Utilihive provides both the technical infrastructure platform (connectivity, integration, data ingestion, data lake, API management) and pre-configured integration content or accelerators (connectors, data flows, orchestrations, utility data model, energy data services, monitoring and reporting dashboards) to speed up the delivery of innovative data driven services and simplify operations. Utilities play a vital role towards achieving the Sustainable Development Goals and now have the opportunity to build universal platforms to facilitate the data economy in a new world including renewable energy. Seamless access to data is crucial to accelerate the digital transformation.
  • 10
    Lyftrondata

    Lyftrondata

    Lyftrondata

    Whether you want to build a governed delta lake, data warehouse, or simply want to migrate from your traditional database to a modern cloud data warehouse, do it all with Lyftrondata. Simply create and manage all of your data workloads on one platform by automatically building your pipeline and warehouse. Analyze it instantly with ANSI SQL, BI/ML tools, and share it without worrying about writing any custom code. Boost the productivity of your data professionals and shorten your time to value. Define, categorize, and find all data sets in one place. Share these data sets with other experts with zero codings and drive data-driven insights. This data sharing ability is perfect for companies that want to store their data once, share it with other experts, and use it multiple times, now and in the future. Define dataset, apply SQL transformations or simply migrate your SQL data processing logic to any cloud data warehouse.
  • 11
    Huawei Cloud Data Lake Governance Center
    Simplify big data operations and build intelligent knowledge libraries with Data Lake Governance Center (DGC), a one-stop data lake operations platform that manages data design, development, integration, quality, and assets. Build an enterprise-class data lake governance platform with an easy-to-use visual interface. Streamline data lifecycle processes, utilize metrics and analytics, and ensure good governance across your enterprise. Define and monitor data standards, and get real-time alerts. Build data lakes quicker by easily setting up data integrations, models, and cleaning rules, to enable the discovery of new reliable data sources. Maximize the business value of data. With DGC, end-to-end data operations solutions can be designed for scenarios such as smart government, smart taxation, and smart campus. Gain new insights into sensitive data across your entire organization. DGC allows enterprises to define business catalogs, classifications, and terms.
    Starting Price: $428 one-time payment
  • 12
    Databricks Data Intelligence Platform
    The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
  • 13
    Delta Lake

    Delta Lake

    Delta Lake

    Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. Data lakes typically have multiple data pipelines reading and writing data concurrently, and data engineers have to go through a tedious process to ensure data integrity, due to the lack of transactions. Delta Lake brings ACID transactions to your data lakes. It provides serializability, the strongest level of isolation level. Learn more at Diving into Delta Lake: Unpacking the Transaction Log. In big data, even the metadata itself can be "big data". Delta Lake treats metadata just like data, leveraging Spark's distributed processing power to handle all its metadata. As a result, Delta Lake can handle petabyte-scale tables with billions of partitions and files at ease. Delta Lake provides snapshots of data enabling developers to access and revert to earlier versions of data for audits, rollbacks or to reproduce experiments.
  • 14
    Kylo

    Kylo

    Teradata

    Kylo is an open source enterprise-ready data lake management software platform for self-service data ingest and data preparation with integrated metadata management, governance, security and best practices inspired by Think Big's 150+ big data implementation projects. Self-service data ingest with data cleansing, validation, and automatic profiling. Wrangle data with visual sql and an interactive transform through a simple user interface. Search and explore data and metadata, view lineage, and profile statistics. Monitor health of feeds and services in the data lake. Track SLAs and troubleshoot performance. Design batch or streaming pipeline templates in Apache NiFi and register with Kylo to enable user self-service. Organizations can expend significant engineering effort moving data into Hadoop yet struggle to maintain governance and data quality. Kylo dramatically simplifies data ingest by shifting ingest to data owners through a simple guided UI.
  • 15
    Varada

    Varada

    Varada

    Varada’s dynamic and adaptive big data indexing solution enables to balance performance and cost with zero data-ops. Varada’s unique big data indexing technology serves as a smart acceleration layer on your data lake, which remains the single source of truth, and runs in the customer cloud environment (VPC). Varada enables data teams to democratize data by operationalizing the entire data lake while ensuring interactive performance, without the need to move data, model or manually optimize. Our secret sauce is our ability to automatically and dynamically index relevant data, at the structure and granularity of the source. Varada enables any query to meet continuously evolving performance and concurrency requirements for users and analytics API calls, while keeping costs predictable and under control. The platform seamlessly chooses which queries to accelerate and which data to index. Varada elastically adjusts the cluster to meet demand and optimize cost and performance.
  • 16
    AWS Lake Formation
    AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. A data lake lets you break down data silos and combine different types of analytics to gain insights and guide better business decisions. Setting up and managing data lakes today involves a lot of manual, complicated, and time-consuming tasks. This work includes loading data from diverse sources, monitoring those data flows, setting up partitions, turning on encryption and managing keys, defining transformation jobs and monitoring their operation, reorganizing data into a columnar format, deduplicating redundant data, and matching linked records. Once data has been loaded into the data lake, you need to grant fine-grained access to datasets, and audit access over time across a wide range of analytics and machine learning (ML) tools and services.
  • 17
    FutureAnalytica

    FutureAnalytica

    FutureAnalytica

    Ours is the world’s first & only end-to-end platform for all your AI-powered innovation needs — right from data cleansing & structuring, to creating & deploying advanced data-science models, to infusing advanced analytics algorithms with built-in Recommendation AI, to deducing the outcomes with easy-to-deduce visualization dashboards, as well as Explainable AI to backtrack how the outcomes were derived, our no-code AI platform can do it all! Our platform offers a holistic, seamless data science experience. With key features like a robust Data Lakehouse, a unique AI Studio, a comprehensive AI Marketplace, and a world-class data-science support team (on a need basis), FutureAnalytica is geared to reduce your time, efforts & costs across your data-science & AI journey. Initiate discussions with the leadership, followed by a quick technology assessment in 1–3 days. Build ready-to-integrate AI solutions using FA's fully automated data science & AI platform in 10–18 days.
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