Best Data Warehouse Software for Azure Data Lake

Find and compare the best Data Warehouse software for Azure Data Lake in 2025

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

  • 1
    Azure Synapse Analytics Reviews
    Azure Synapse is the Azure SQL Data Warehouse. Azure Synapse, a limitless analytics platform that combines enterprise data warehouse and Big Data analytics, is called Azure Synapse. It allows you to query data at your own pace, with either serverless or provisioned resources - at scale. Azure Synapse combines these two worlds with a single experience to ingest and prepare, manage and serve data for machine learning and BI needs.
  • 2
    Openbridge Reviews

    Openbridge

    Openbridge

    $149 per month
    Discover insights to boost sales growth with code-free, fully automated data pipelines to data lakes and cloud warehouses. Flexible, standards-based platform that unifies sales and marketing data to automate insights and smarter growth. Say goodbye to manual data downloads that are expensive and messy. You will always know exactly what you'll be charged and only pay what you actually use. Access to data-ready data is a great way to fuel your tools. We only work with official APIs as certified developers. Data pipelines from well-known sources are easy to use. These data pipelines are pre-built, pre-transformed and ready to go. Unlock data from Amazon Vendor Central and Amazon Seller Central, Instagram Stories. Teams can quickly and economically realize the value of their data with code-free data ingestion and transformation. Databricks, Amazon Redshift and other trusted data destinations like Databricks or Amazon Redshift ensure that data is always protected.
  • 3
    BigLake Reviews

    BigLake

    Google

    $5 per TB
    BigLake is a storage platform that unifies data warehouses, lakes and allows BigQuery and open-source frameworks such as Spark to access data with fine-grained control. BigLake offers accelerated query performance across multicloud storage and open formats like Apache Iceberg. You can store one copy of your data across all data warehouses and lakes. Multi-cloud governance and fine-grained access control for distributed data. Integration with open-source analytics tools, and open data formats is seamless. You can unlock analytics on distributed data no matter where it is stored. While choosing the best open-source or cloud-native analytics tools over a single copy, you can also access analytics on distributed data. Fine-grained access control for open source engines such as Apache Spark, Presto and Trino and open formats like Parquet. BigQuery supports performant queries on data lakes. Integrates with Dataplex for management at scale, including logical organization.
  • 4
    Dimodelo Reviews

    Dimodelo

    Dimodelo

    $899 per month
    Instead of getting bogged down in data warehouse code, keep your eyes on the important and compelling reporting, analytics, and insights. Your data warehouse should not become a mess of hundreds of unmanageable stored procedures, notebooks, stored processes, tables, and other complicated pieces. Views and other information. The effort required to design, build and manage a data warehouse is dramatically reduced with Dimodelo DW Studio. You can design, build, and deploy a data warehouse that targets Azure Synapse Analytics. Dimodelo Data Warehouse Studio creates a best-practice architecture using Azure Data Lake, Polybase, and Azure Synapse Analytics. This results in a modern, high-performance data warehouse in the cloud. Dimodelo Data Warehouse Studio creates a best-practice architecture that delivers a modern, high-performance data warehouse in the cloud by using parallel bulk loads and in memory tables.
  • 5
    Apache Hudi Reviews

    Apache Hudi

    Apache Corporation

    Hudi is a rich platform for building streaming data lakes using incremental data pipelines on a self managing database layer. It can also be optimized for regular batch processing and lake engines. Hudi keeps a timeline of all actions on the table at different times. This allows for instantaneous views and efficient retrieval of data in the order they were received. The following components make up a Hudi instant. Hudi provides efficient upserts by mapping a given Hoodie key consistently with a file ID, via an indexing mechanism. Once a record is written to a file, the mapping between record key/file group/file ID never changes. The mapped file group includes all versions of a group record.
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