Top 10 Alternatives to Hive Recently Reviewed By G2 Community
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How it works
Snowflake’s platform eliminates data silos and simplifies architectures, so organizations can get more value from their data. The platform is designed as a single, unified product with automations that reduce complexity and help ensure everything “just works”. To support a wide range of workloads, it’s optimized for performance at scale no matter whether someone’s working with SQL, Python, or other languages. And it’s globally connected so organizations can securely access the most relevant content across clouds and regions, with one consistent experience.
Analyze Big Data in the cloud with BigQuery. Run fast, SQL-like queries against multi-terabyte datasets in seconds. Scalable and easy to use, BigQuery gives you real-time insights about your data.
Teradata Autonomous Knowledge Platform easily and efficiently handles complex data requirements and simplifies management of the data warehouse environment.
Offer a fast, reliable, and cost-effective platform for data warehousing and business intelligence that is easy to scale to meet the complex reporting.
Vertica offers a software-based analytics platform designed to help organizations of all sizes monetize data in real time and at massive scale.
Amazon Redshift is a fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools.
IBM® Db2® is the database that offers enterprise-wide solutions handling high-volume workloads. It is optimized to deliver industry-leading performance while lowering costs.
Making big data simple
Dremio is a data analysis software. It is self-service data platform provided that users discover, accelerate and share data at any time.
VMware Greenplum provides comprehensive and integrated analytics on multi-structured data. Powered by one of the world's most advanced cost-based query optimizers, VMware Greenplum delivers unmatched analytical query performance on massive volumes of data.