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Apache Hive VS ClickHouse Cloud

Compare Apache Hive VS ClickHouse Cloud and see what are their differences

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Apache Hive logo Apache Hive

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

ClickHouse Cloud logo ClickHouse Cloud

Serverless Hosted ClickHouse Offering. Cloud-agnostic, No infrastructure to manage, Automatic scaling, Consumption-based pricing, Turnkey data migration services, World-class security and privacy guarantees.
  • Apache Hive Landing page
    Landing page //
    2023-01-13
Not present

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.

ClickHouse Cloud features and specs

No features have been listed yet.

Apache Hive videos

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Hive vs Impala - Comparing Apache Hive vs Apache Impala

ClickHouse Cloud videos

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Category Popularity

0-100% (relative to Apache Hive and ClickHouse Cloud)

Apache Hive

ClickHouse Cloud

Databases
100 100%
Databases
0% 0
Big Data As A Service
0 0%
Big Data As A Service
100% 100
Big Data
88 88%
Big Data
12% 12
Relational Databases
100 100%
Relational Databases
0% 0

User comments

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Social recommendations and mentions

Based on our record, Apache Hive should be more popular than ClickHouse Cloud. It has been mentiond 8 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.

Apache Hive mentions (8)

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ClickHouse Cloud mentions (2)

  • Show HN: We built a ClickHouse-based logging service
    > Note: hosted CH did not exist yet. We are using Altinity to run our cluster. It exists now actually. We (highlight) are on hosted clickhouse, which went in GA a few months ago. https://clickhouse.com/cloud. - Source: Hacker News / over 2 years ago
  • How ClickHouse helps us track billions of GraphQL requests monthly
    After looking for alternatives we decided to switch to ClickHouse. We highly recommend reading the "100x Faster: GraphQL Hive migration from Elasticsearch to ClickHouse" article we wrote with the ClickHouse Cloud team. It covers in detail the problems we were facing and the decision-making process that lead us to love ClickHouse. - Source: dev.to / almost 3 years ago

What are some alternatives?

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

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

Amazon Redshift - Learn about Amazon Redshift cloud data warehouse.

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

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.

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

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

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