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Apache Hive VS Apache Doris

Compare Apache Hive VS Apache Doris and see what are their differences

Apache Hive logo Apache Hive

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

Apache Doris logo Apache Doris

Apache Doris is an open-source real-time data warehouse for big data analytics.
  • Apache Hive Landing page
    Landing page //
    2023-01-13
  • Apache Doris Apache Doris
    Apache Doris //
    2024-01-10

Apache Hive features and specs

  • Scalability
    Apache Hive is built on top of Hadoop, allowing it to efficiently handle large datasets by distributing the load across a cluster of machines.
  • SQL-like Interface
    Hive provides a familiar SQL-like querying language, HiveQL, which makes it easier for users with SQL knowledge to perform data analysis on large datasets without needing to learn a new syntax.
  • Integration with Hadoop Ecosystem
    Hive integrates seamlessly with other components of the Hadoop ecosystem such as HDFS for storage and MapReduce for processing, making it a versatile tool for big data processing.
  • Schema on Read
    Hive uses a schema-on-read model which allows it to work with flexible data schemas and handle unstructured or semi-structured data efficiently.
  • Extensibility
    Users can extend Hive's capabilities by writing custom UDFs (User Defined Functions), UDAFs (User Defined Aggregate Functions), and SerDes (Serializers/ Deserializers).

Possible disadvantages of Apache Hive

  • Latency in Query Processing
    Queries in Hive often take longer to execute compared to traditional databases, as they are converted to MapReduce jobs which can introduce significant latency.
  • Limited Real-time Processing
    Hive is designed for batch processing and is not suitable for real-time analytics due to its reliance on MapReduce, which is not optimized for low-latency operations.
  • Complex Configuration
    Setting up Hive and configuring it to work optimally within a Hadoop cluster can be complex and require a significant amount of effort and expertise.
  • Lack of Support for Transactions
    Hive does not natively support full ACID transactions, which can be a limitation for applications that require consistent transaction management across large datasets.
  • Dependency on Hadoop
    Hive's reliance on the Hadoop ecosystem means it inherits some of Hadoop's limitations, such as a steep learning curve and the need for substantial resources to manage a cluster.

Apache Doris features and specs

No features have been listed yet.

Apache Hive videos

Hive vs Impala - Comparing Apache Hive vs Apache Impala

Apache Doris videos

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Category Popularity

0-100% (relative to Apache Hive and Apache Doris)
Databases
57 57%
43% 43
Big Data
100 100%
0% 0
Relational Databases
46 46%
54% 54
Data Warehousing
48 48%
52% 52

User comments

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Reviews

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

Apache Hive 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

Apache Hive might be a bit more popular than Apache Doris. We know about 8 links to it since March 2021 and only 6 links to Apache Doris. 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.

Apache Hive mentions (8)

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Apache Doris mentions (6)

  • Evolution of Data Sharding Towards Automation and Flexibility
    Like in many databases, Apache Doris shards data into partitions, and then a partition is further divided into buckets. Partitions are typically defined by time or other continuous values. This allows query engines to quickly locate the target data during queries by pruning irrelevant data ranges. - Source: dev.to / 8 months ago
  • Steps to industry-leading query speed: evolution of the Apache Doris execution engine
    What makes a modern database system? The three key modules are query optimizer, execution engine, and storage engine. Among them, the role of execution engine to the DBMS is like the chef to a restaurant. This article focuses on the execution engine of the Apache Doris data warehouse, explaining the secret to its high performance. - Source: dev.to / 9 months ago
  • Apache Doris for log and time series data analysis in NetEase, why not Elasticsearch and InfluxDB?
    For most people looking for a log management and analytics solution, Elasticsearch is the go-to choice. The same applies to InfluxDB for time series data analysis. These were exactly the choices of NetEase, one of the world's highest-yielding game companies but more than that. As NetEase expands its business horizons, the logs and time series data it receives explode, and problems like surging storage costs and... - Source: dev.to / 10 months ago
  • Multi-tenant workload isolation in Apache Doris: a better balance between isolation and utilization
    This is an in-depth introduction to the workload isolation capabilities of Apache Doris. But first of all, why and when do you need workload isolation? If you relate to any of the following situations, read on and you will end up with a solution:. - Source: dev.to / 11 months ago
  • 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 / 11 months ago
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What are some alternatives?

When comparing Apache Hive and Apache Doris, you can also consider the following products

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

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

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.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.