Software Alternatives, Accelerators & Startups
Register | Login

Apache Doris VS Greenplum Database

Compare Apache Doris VS Greenplum Database and see what are their differences

Grapple
Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI featured
Contents:
  1. » Base Details
  2. » Reviews
  3. » Alternatives

Apache Doris logo Apache Doris

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

Greenplum Database logo Greenplum Database

Greenplum Database is an open source parallel data warehousing platform.
  • Apache Doris Apache Doris
    Apache Doris //
    2024-01-10
  • Greenplum Database Landing page
    Landing page //
    2023-07-29

Apache Doris features and specs

  • High Performance
    Apache Doris is designed to deliver high query performance, especially for aggregate queries, due to its columnar storage and vectorized execution engine.
  • Real-time Analytics
    Supports real-time data analytics with low latency, thanks to its efficient data ingestion processes and real-time data update capabilities.
  • Unified Analytics
    Provides a unified platform that supports both real-time and batch data processing, offering flexibility for different analytical workloads.
  • Ease of Use
    Features a SQL-like interface, which makes it accessible for users familiar with SQL, reducing the learning curve.
  • Scalability
    Can scale out horizontally, allowing it to handle increasing volumes of data and user queries by adding more nodes to the cluster.

Possible disadvantages of Apache Doris

  • Ecosystem Integration
    While improving, the ecosystem isn't as mature as older database management systems, which might pose integration challenges with certain tools.
  • Community Support
    Being a relatively newer project, it may not have as large a community or as extensive third-party support as more established databases.
  • Complexity in Setup
    Initial setup and configuration can be complex, especially for users not already familiar with similar distributed systems.
  • Limited Use Cases
    Optimized specifically for online analytical processing (OLAP), it may not be suitable for all types of databases or transactional use cases.
  • Features Maturity
    Some features may lack the maturity and robustness found in more mature and widely adopted database systems, requiring careful evaluation based on project needs.

Greenplum Database features and specs

  • Scalability
    Greenplum Database is designed for massive parallel processing, allowing the system to scale horizontally by adding more nodes to handle large amounts of data efficiently.
  • Open Source
    As an open-source database, Greenplum provides a cost-effective solution for businesses looking to leverage powerful analytics without proprietary software limitations.
  • Advanced Analytics
    Greenplum supports a wide range of data science and machine learning capabilities, making it suitable for complex analytical processing and large-scale data mining.
  • Integration with Hadoop
    Greenplum offers integration capabilities with Hadoop, allowing users to effectively manage and analyze data within hybrid environments.
  • Enterprise Features
    It comes with robust enterprise features including support for ACID compliance, high availability, and backup and recovery capabilities, catering to demanding business needs.

Possible disadvantages of Greenplum Database

  • Complex Setup and Maintenance
    The initial setup and ongoing maintenance can be complex and may require specialized expertise, which could be a barrier for companies with limited technical resources.
  • Resource Intensive
    Greenplum's performance heavily relies on proper resource allocation, and it can be resource-intensive, requiring significant computational power and storage.
  • Requires Expertise
    Effective use of Greenplum often requires a skilled team to manage and optimize the database, which might not be ideal for small teams or organizations.
  • Limited Cloud-Native Features
    Compared to some modern cloud-native databases, Greenplum may lack certain features tailored to cloud environments, which can limit its integration in purely cloud-based setups.
  • Upgrade Processes
    The process for upgrading Greenplum can be complex and time-consuming, potentially causing disruptions if not carefully managed.

Category Popularity

0-100% (relative to Apache Doris and Greenplum Database)

Apache Doris

Greenplum Database

Databases
58 58%
Databases
42% 42
Relational Databases
61 61%
Relational Databases
39% 39
Data Warehousing
66 66%
Data Warehousing
34% 34
Big Data
0 0%
Big Data
100% 100

User comments

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

Reviews

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

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.
Source: doris.apache.org

Greenplum Database Reviews

We have no reviews of Greenplum Database yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Doris should be more popular than Greenplum Database. 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 Doris mentions (8)

  • Doris x Gravitino: Unified Metadata Management for Modern Lakehouse Architecture
    This article provides an in-depth introduction to deep integration between Apache Doris and Apache Gravitino, building a modern lakehouse architecture based on Iceberg REST Catalog. Through Gravitino's unified metadata management and dynamic credential vending capabilities, we achieve efficient and secure access to Iceberg data stored on S3. - Source: dev.to / 5 days ago
  • Gravitino 0.5.0: Expanding the horizon to Apache Spark, non-tabular data, and more!
    Tagging onto our Real-Time Analytics support, we are now also supporting Apache Doris in this release. Doris is a high-performance, real-time analytical data warehouse that is known for its speed and ease of use. By adding a Doris catalog, engineers implementing Gravitino will now have more flexibility in their cataloging options for their analytical workloads. (Issue #1339, visit jdbc-doris-catalog for... - Source: dev.to / about 2 months ago
  • 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 / about 1 year 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 / about 1 year 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 / about 1 year ago
View more

Greenplum Database mentions (4)

  • Ask HN: It's 2023, how do you choose between MySQL and Postgres?
    Friends don't let their friends choose Mysql :) A super long time ago (decades) when I was using Oracle regularly I had to make a decision on which way to go. Although Mysql then had the mindshare I thought that Postgres was more similar to Oracle, more standards compliant, and more of a real enterprise type of DB. The rumor was also that Postgres was heavier than MySQL. Too many horror stories of lost data... - Source: Hacker News / over 2 years ago
  • Amazon Aurora's Read/Write Capability Enhancement with Apache ShardingSphere-Proxy
    A database solution architect at AWS, with over 10 years of experience in the database industry. Lili has been involved in the R&D of the Hadoop/Hive NoSQL database, enterprise-level database DB2, distributed data warehouse Greenplum/Apache HAWQ and Amazon’s cloud native database. - Source: dev.to / over 3 years ago
  • What’s the Database Plus concept and what challenges can it solve?
    Today, it is normal for enterprises to leverage diversified databases. In my market of expertise, China, in the Internet industry, MySQL together with data sharding middleware is the go to architecture, with GreenPlum, HBase, Elasticsearch, Clickhouse and other big data ecosystems being auxiliary computing engine for analytical data. At the same time, some legacy systems (such as SQLServer legacy from .NET... - Source: dev.to / over 3 years ago
  • Inspecting joins in PostgreSQL
    PostgreSQL is a free and advanced database system with the capacity to handle a lot of data. It’s available for very large data in several forms like Greenplum and Redshift on Amazon. It is open source and is managed by an organized and very principled community. - Source: dev.to / over 3 years ago

What are some alternatives?

When comparing Apache Doris and Greenplum Database, 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 Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

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.

Microsoft Azure Data Lake - Azure Data Lake is a real-time data processing and analytics solution that works across platforms and languages.

MySQL - The world's most popular open source database

FME by Safe - FME is an integrated collection of Spatial ETL tools for data transformation and data translation.

Loading...