Best Columnar Databases for Mage Platform

Find and compare the best Columnar Databases for Mage Platform in 2024

Use the comparison tool below to compare the top Columnar Databases for Mage Platform on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Google Cloud BigQuery Reviews

    Google Cloud BigQuery

    Google

    $0.04 per slot hour
    1,686 Ratings
    See Software
    Learn More
    ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys
  • 2
    Snowflake Reviews

    Snowflake

    Snowflake

    $40.00 per month
    4 Ratings
    Your cloud data platform. Access to any data you need with unlimited scalability. All your data is available to you, with the near-infinite performance and concurrency required by your organization. You can seamlessly share and consume shared data across your organization to collaborate and solve your most difficult business problems. You can increase productivity and reduce time to value by collaborating with data professionals to quickly deliver integrated data solutions from any location in your organization. Our technology partners and system integrators can help you deploy Snowflake to your success, no matter if you are moving data into Snowflake.
  • 3
    Amazon Redshift Reviews

    Amazon Redshift

    Amazon

    $0.25 per hour
    Amazon Redshift is preferred by more customers than any other cloud data storage. Redshift powers analytic workloads for Fortune 500 companies and startups, as well as everything in between. Redshift has helped Lyft grow from a startup to multi-billion-dollar enterprises. It's easier than any other data warehouse to gain new insights from all of your data. Redshift allows you to query petabytes (or more) of structured and semi-structured information across your operational database, data warehouse, and data lake using standard SQL. Redshift allows you to save your queries to your S3 database using open formats such as Apache Parquet. This allows you to further analyze other analytics services like Amazon EMR and Amazon Athena. Redshift is the fastest cloud data warehouse in the world and it gets faster each year. The new RA3 instances can be used for performance-intensive workloads to achieve up to 3x the performance compared to any cloud data warehouse.
  • 4
    Apache HBase Reviews

    Apache HBase

    The Apache Software Foundation

    Apache HBase™, is used when you need random, real-time read/write access for your Big Data. This project aims to host very large tables, billions of rows and X million columns, on top of clusters of commodity hardware.
  • 5
    Apache Parquet Reviews

    Apache Parquet

    The Apache Software Foundation

    Parquet was created to provide the Hadoop ecosystem with the benefits of columnar, compressed data representation. Parquet was built with complex nested data structures and uses the Dremel paper's record shredding/assemblage algorithm. This approach is better than flattening nested namespaces. Parquet is designed to support efficient compression and encoding strategies. Multiple projects have shown the positive impact of the right compression and encoding scheme on data performance. Parquet allows for compression schemes to be specified per-column. It is future-proofed to allow for more encodings to be added as they are developed and implemented. Parquet was designed to be used by everyone. We don't want to play favorites in the Hadoop ecosystem.
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