# Data Warehouse & Data Lake Platforms SaaS

> 1,098 Data Warehouse & Data Lake Platforms SaaS products listed on SaaS Browser, 93 added in the last 30 days. Figures as of 2026-11-07.

Web page: https://saasbrowser.com/en/category/data-warehouse-data-lake-platforms
All categories: https://saasbrowser.com/en/categories.md

## Key figures

- SaaS products: 1,098
- Added in the last 30 days: 93
- Median domain rating (0-100): 21.0
- Median domain rating across all SaaS: 14.0
- Median company age: 6.0 years
- Running an affiliate program: 3.6%
- Median affiliate commission: 5.0%
- Customers: B2B and B2C 6.7%, B2B 93.3%
- Top countries: United States (273), India (28), United Kingdom (24), Canada (19), Germany (17)

## Most established

- MongoDB Atlas
- Couchbase
- Snowflake AI Data Cloud
- Databricks
- Cloudera
- Confluent
- Informa
- ClickHouse
- Fivetran
- dbt Labs

## Recently added

- EverySchema
- Ciphergram
- Sparebyte
- DuckCast
- Clart
- Walmart Global Tech
- Blue Komodo Stack
- DataRig
- Hilbium
- Suiteoryx

## Products (page 1 of 10)

- [Confluent](https://saasbrowser.com/en/saas/29360/confluent): This platform facilitates the seamless integration, processing, and governance of real-time data streams, enabling organizations to build efficient data architectures and applications. Key features include data streaming capabilities, connectors for ecosystem integration, governance tools for data quality, and support for event-driven microservices, addressing challenges such as data silos, latency issues, and the need for reliable data access, making it ideal for businesses across various industries seeking to leverage data for enhanced decision-making and operational efficiency.
- [Hazelcast](https://saasbrowser.com/en/saas/69137/hazelcast): Hazelcast offers a unified real-time data platform designed for instant action, enabling organizations to streamline development and enhance performance across various applications. With features such as distributed computing, fast data storage, and AI capabilities, the platform supports modern enterprise architectures while ensuring scalability and resilience in cloud-agnostic environments.
- [Snowflake AI Data Cloud](https://saasbrowser.com/en/saas/166976/snowflake-ai-data-cloud): A comprehensive platform facilitates the development and deployment of AI applications and data solutions by seamlessly integrating various data types and sources. Key features include robust data engineering capabilities, advanced analytics tools, secure collaboration environments, and streamlined model development, all designed to enhance operational efficiency and drive innovation for businesses across diverse industries. This solution addresses challenges related to data silos, complex infrastructure management, and the need for real-time insights, making it ideal for organizations seeking to leverage data for strategic decision-making and competitive advantage.
- [dbt Labs](https://saasbrowser.com/en/saas/32756/dbt-labs): dbt Labs offers a powerful platform for transforming data within warehouses, enabling organizations to streamline their data development processes and enhance collaboration. With features designed to boost efficiency and reliability, dbt Cloud empowers data teams to deliver high-quality, trusted data products that drive informed business decisions.
- [VAST Data](https://saasbrowser.com/en/saas/121457/vast-data): The VAST Data Platform offers a unified solution for managing unstructured data, integrating storage, database, and compute capabilities into a single scalable architecture designed for AI and deep learning. With a focus on eliminating data silos and simplifying management, it empowers organizations to harness the full potential of their data in modern data centers and cloud environments.
- [APEX QUERY LLC](https://saasbrowser.com/en/saas/1601845/apex-query-llc): APEX QUERY provides comprehensive insights into data warehouse performance by analyzing compute utilization, identifying idle and over-provisioned resources, and recommending cost-effective optimizations to reduce expenses and improve efficiency. Its main features include automated assessments of warehouse configurations, detailed cost attribution per workload and task, actionable SQL script suggestions for performance tuning, visualization of query execution patterns, and workload classification to pinpoint optimization opportunities, making it ideal for data engineers, database administrators, and analytics teams aiming to optimize cloud data platform costs and performance.
- [mydo](https://saasbrowser.com/en/saas/1602581/mydo): This data management platform provides comprehensive visualization and tracing capabilities for complex data ecosystems, allowing teams to gain instant visibility into data origins, flows, and potential issues across diverse tools and systems. Its main features include real-time data lineage, automated root cause analysis powered by artificial intelligence, schema drift detection, impact analysis, metadata management through ownership and governance tagging, over 165 connectors for cross-platform integration, and self-service analytics for non-technical users, addressing problems such as pipeline debugging, data quality, data freshness, schema changes, and governance challenges. It is designed for data engineers, analysts, data governance teams, and business users seeking to improve data reliability, reduce troubleshooting time, ensure data quality, and enhance operational efficiencies within large and complex data infrastructures.
- [Evid](https://saasbrowser.com/en/saas/1707178/evid): This product provides governed AI-driven analytics for large-scale data warehouses, enabling users to ask natural language questions and receive accurate, evidence-backed answers based on pre-approved tables and business rules. Its main features include context management, rule enforcement, and seamless integration with data platforms like BigQuery, Postgres, MySQL, and Snowflake, solving problems related to ungoverned data querying, inconsistent results, and lack of transparency, making it ideal for data analysts, business intelligence teams, and decision-makers seeking reliable, compliant insights quickly and efficiently.
- [DataStori](https://saasbrowser.com/en/saas/619076/datastori): This platform facilitates the seamless ingestion and storage of data from various applications, ensuring a fast, reliable, and scalable solution for data management. Key features include over 1,000 connectors for diverse cloud and on-premises applications, automated pipeline management with alerts and retries, and robust data security that adheres to customer governance policies, making it ideal for businesses seeking efficient data integration and management solutions.
- [DataKru](https://saasbrowser.com/en/saas/1613493/datakru): This platform facilitates seamless data management and transformation by providing a unified workspace for uploading, standardizing, exploring, and shipping data without relying on complex code or multiple tools. Its key features include file uploads (such as CSVs), data quality checks, field standardization, flexible data mapping, transformation capabilities, and visualization tools that enable users to analyze information quickly and effectively. Designed for solo data builders and small teams, it addresses challenges related to messy inputs, inconsistent data formats, and manual data processing, empowering users to efficiently prepare and utilize data for reporting, analytics, and integration purposes.
- [CaduCore](https://saasbrowser.com/en/saas/1510164/caducore): The platform facilitates digital data management by enabling users to create, organize, and control datasets within a secure, unified workspace designed for modern team collaboration. Its key features include comprehensive dataset creation tools, integrated security measures for access control, and a streamlined interface that simplifies navigation from sign-in to data action, ultimately solving problems related to information chaos, inconsistent data handling, and security vulnerabilities; it is ideal for organizations, data teams, and enterprise users seeking efficient, secure, and scalable data management solutions.
- [DeltaForge](https://saasbrowser.com/en/saas/1551195/deltaforge): This native data processing engine enables high-performance reading and writing of Delta Lake and Apache Iceberg tables directly on existing hardware without requiring clusters or additional data warehouses. It offers features such as in-place data modifications, seamless table versioning with time travel, schema enforcement, change data feed, and interoperability between different data formats, solving challenges related to data consistency, validation, and operational complexity in lakehouse architectures. Designed for data engineers, scientists, and analytics teams, it provides a cost-effective, reliable, and verifiable platform for managing large-scale analytics workloads, data lake management, and real-time data access without the need for complex cluster management or data duplication.
- [Adamatics](https://saasbrowser.com/en/saas/99825/adamatics): This unified data platform consolidates disparate data sources, analytics tools, and collaborative workflows into a single, integrated environment, enabling teams to work together more efficiently and make data-driven decisions rapidly. Key features include seamless data integration across cloud and on-premises systems, role-based security and permissions, real-time collaboration through shared notebooks and models, and support for experimentation and deployment without reliance on IT bottlenecks, solving problems related to siloed data, disconnected tools, and isolated teams. It is designed for data analysts, data scientists, engineers, and business professionals seeking to streamline analytics workflows, improve collaboration, and accelerate insights within complex organizational infrastructures.
- [DataSwitch](https://saasbrowser.com/en/saas/1180313/dataswitch): This data management and analytics platform automates and streamlines complex data transformation, migration, and governance processes within hybrid and cloud-native environments. Its main features include intelligent data traceability, no-code data engineering, automated data migration, real-time visibility, and flexible customization, effectively reducing technical debt, accelerating deployment times, and improving data accuracy for data professionals, enterprise technology teams, and organizations seeking reliable, secure, and efficient data services.
- [Fleak](https://saasbrowser.com/en/saas/309821/fleak): A universal data ingestion, transformation, and normalization platform that pulls in diverse sources, harmonizes and cleans data, automatically detects and corrects schema drift, and deploys consistent, AI-ready outputs to any destination across on-prem, cloud, hybrid, or edge environments. It eliminates brittle data, silos, and long onboarding times by generating executable transformation logic from documentation and sample data, freeing engineering time to build AI models and products, enabling engine-agnostic, scalable deployments and faster, governance-friendly data pipelines for data teams, security professionals, IT operations, and enterprise analytics stakeholders.
- [DataWarehousePro](https://saasbrowser.com/en/saas/563401/datawarehousepro): DataWarehousePro offers an easy way to store, manage, and share data securely. Users can upload their data, create visualizations, and control access, making it a flexible solution for individuals and organizations alike.
- [XLTable](https://saasbrowser.com/en/saas/1353935/xltable): XLTable functions as an advanced OLAP server that enables seamless integration of modern analytical databases like ClickHouse, BigQuery, and Snowflake with Excel, transforming large datasets into interactive pivot tables without requiring complex SQL knowledge or report rewriting. Its main features include native Excel connectivity via the XMLA protocol, flexible cube modeling with measures, hierarchies, and attributes, secure role-based access control through enterprise directory integration, and the ability to handle vast amounts of data efficiently, solving problems related to analyzing big data, simplifying data modeling, and enhancing accessibility for business analysts and data professionals working within familiar spreadsheet environments.
- [Data Harbor](https://saasbrowser.com/en/saas/13408/data-harbor): Data Harbor offers innovative solutions for real-time, AI-powered data handling, enabling enterprises to consolidate and streamline their customer data effortlessly. With a focus on maximizing the value of enterprise data while minimizing investment, the platform provides a user-friendly experience for building and deploying rich customer profiles in both analytical and production environments.
- [spice ai](https://saasbrowser.com/en/saas/427716/spice-ai): A unified data platform that federates SQL across operational databases, data lakes, and warehouses, delivering local acceleration for multi-source queries, hybrid search that blends vector similarity, full-text, and keyword search in a single SQL engine, embedded AI inference via SQL UDFs, secure AI sandboxing with least-privilege data access, and edge-to-cloud deployments with real-time change data capture and distributed query capabilities. It solves data silos, latency, governance, and trust challenges in AI-powered workloads by enabling retrieval-augmented generation, AI model serving, secure AI agents, and scalable data-grounded AI across environments, and is intended for developers, data engineers, data scientists, security and IT teams building applications in industries like cybersecurity, financial services, and SaaS.
- [Acuratio](https://saasbrowser.com/en/saas/59022/acuratio): Acuratio's Multicloud Federated Learning Platform empowers organizations to harness the value of their data while maintaining privacy and compliance. By enabling the combination of diverse datasets, the platform facilitates the development of accurate machine learning models and aggregate statistics without compromising individual or model confidentiality.

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