Software Alternatives, Accelerators & Startups
Register | Login

VeloDB VS Apache Hive

Compare VeloDB VS Apache Hive and see what are their differences

TradingJournal
TradingJournal is a modern trade tracking app that helps traders understand their performance, reduce emotional mistakes, and optimize strategies. With risk analysis, pattern detection, and visual insights. Free and ad-free. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

VeloDB logo VeloDB

Modern Real-Time Data Warehouse

Apache Hive logo Apache Hive

Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.
  • VeloDB VeloDB
    VeloDB //
    2024-01-10

VeloDB is a modern real-time data warehouse powered by open source Apache Doris for lightning-fast data analytics at scale. It ensures big data ingestion within seconds and outstanding performance in both real-time serving and interactive ad-hoc queries. It is one platform for various analytics workloads, including structured and semi-structured data processing, real-time analytics and batch processing, internal data query and federated queries of external data. It allows elastic scaling for efficient resource management. It can dynamically adjust the computing resources allocated to the workload based on the changing requirements. It supports MySQL protocol and standard SQL for easy integration with other data tools. It also provides open data API to be accessible for various external query engines.

  • Apache Hive Landing page
    Landing page //
    2023-01-13

VeloDB features and specs

No features have been listed yet.

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.

VeloDB videos

No VeloDB videos yet. You could help us improve this page by suggesting one.

Add video

Apache Hive videos

+ Add

Hive vs Impala - Comparing Apache Hive vs Apache Impala

Category Popularity

0-100% (relative to VeloDB and Apache Hive)

VeloDB

Apache Hive

Data Warehousing
48 48%
Data Warehousing
52% 52
Databases
31 31%
Databases
69% 69
Relational Databases
47 47%
Relational Databases
53% 53
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using VeloDB and Apache Hive. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Apache Hive seems to be more popular. 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.

VeloDB mentions (0)

We have not tracked any mentions of VeloDB yet. Tracking of VeloDB recommendations started around Jan 2024.

Apache Hive mentions (8)

View more

What are some alternatives?

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

Snowflakepowe.red - Snowflake Computing is delivering a data warehouse for the cloud.

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

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

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

Presto - Next generation front-of-house technology

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

Loading...