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IBM Db2 Warehouse on Cloud VS StarRocks

Compare IBM Db2 Warehouse on Cloud VS StarRocks and see what are their differences

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IBM Db2 Warehouse on Cloud logo IBM Db2 Warehouse on Cloud

IBM Db2 Warehouse on Cloud is a fully-managed, cloud data warehouse service powered by IBM BLU Acceleration and built for high-performance analytics and machine learning.

StarRocks logo StarRocks

StarRocks offers the next generation of real-time SQL engines for enterprise-scale analytics. Learn how we make it easy to deliver real-time analytics.
  • IBM Db2 Warehouse on Cloud Landing page
    Landing page //
    2023-09-27
  • StarRocks Landing page
    Landing page //
    2023-09-21

IBM Db2 Warehouse on Cloud videos

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StarRocks videos

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The Secrets Behind StarRocks' Blazing-Fast Query Performance

More videos:

  • Review - How can StarRocks outperform ClickHouse, Apache Druid® and Trino？
  • Review - Achieving real-time analytics using Apache Kafka®, Apache Flink® and StarRocks

Category Popularity

0-100% (relative to IBM Db2 Warehouse on Cloud and StarRocks)

IBM Db2 Warehouse on Cloud

StarRocks

Big Data
100 100%
Big Data
0% 0
Databases
31 31%
Databases
69% 69
Data Management
100 100%
Data Management
0% 0
Relational Databases
0 0%
Relational Databases
100% 100

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What are some alternatives?

When comparing IBM Db2 Warehouse on Cloud and StarRocks, you can also consider the following products

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Apache Doris - Apache Doris is an open-source real-time data warehouse for big data analytics.

Amazon Redshift - Learn about Amazon Redshift cloud data warehouse.

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

Azure SQL Data Warehouse - Azure Synapse Analytics (formerly SQL DW) is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics.

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

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