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Databricks Unified Analytics Platform VS Apache Doris

Compare Databricks Unified Analytics Platform VS Apache Doris and see what are their differences

Databricks Unified Analytics Platform logo Databricks Unified Analytics Platform

One platform for accelerating data-driven innovation across data engineering, data science & business analytics

Apache Doris logo Apache Doris

Apache Doris is an open-source real-time data warehouse for big data analytics.
  • Databricks Unified Analytics Platform Landing page
    Landing page //
    2023-07-11
  • Apache Doris Apache Doris
    Apache Doris //
    2024-01-10

Category Popularity

0-100% (relative to Databricks Unified Analytics Platform and Apache Doris)
Development
100 100%
0% 0
Databases
0 0%
100% 100
Office & Productivity
100 100%
0% 0
Relational Databases
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Databricks Unified Analytics Platform and Apache Doris

Databricks Unified Analytics Platform Reviews

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Apache Doris Reviews

Log analysis: Elasticsearch vs Apache Doris
If you are looking for an efficient log analytic solution, Apache Doris is friendly to anyone equipped with SQL knowledge; if you find friction with the ELK stack, try Apache Doris provides better schema-free support, enables faster data writing and queries, and brings much less storage burden.

Social recommendations and mentions

Based on our record, Apache Doris should be more popular than Databricks Unified Analytics Platform. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Databricks Unified Analytics Platform mentions (1)

  • Should I replicate all our transactional DB to Redshift?
    See more here: https://databricks.com/product/data-lakehouse. Source: about 2 years ago

Apache Doris mentions (2)

  • SQL Convertor for Easy Migration from Presto, Trino, ClickHouse, and Hive to Apache Doris
    Apache Doris is an all-in-one data platform that is capable of real-time reporting, ad-hoc queries, data lakehousing, log management and analysis, and batch data processing. As more and more companies have been replacing their component-heavy data architecture with Apache Doris, there is an increasing need for a more convenient data migration solution. That's why the Doris SQL Convertor is made. - Source: dev.to / 7 days ago
  • Variant in Apache Doris 2.1.0: a new data type 8 times faster than JSON for semi-structured data analysis
    As an open-source real-time data warehouse, Apache Doris provides semi-structured data processing capabilities, and the newly-released version 2.1.0 makes a stride in this direction. Before V2.1, Apache Doris stores semi-structured data as JSON files. However, during query execution, the real-time parsing of JSON data leads to high CPU and I/O consumption in addition to high query latency, especially when the... - Source: dev.to / 2 months ago

What are some alternatives?

When comparing Databricks Unified Analytics Platform and Apache Doris, you can also consider the following products

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

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

Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.

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.

Apache Zeppelin - A web-based notebook that enables interactive data analytics.

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