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Apache Doris VS IBM Cloud Pak for Data

Compare Apache Doris VS IBM Cloud Pak for Data and see what are their differences

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Apache Doris logo Apache Doris

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

IBM Cloud Pak for Data logo IBM Cloud Pak for Data

Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.
  • Apache Doris Apache Doris
    Apache Doris //
    2024-01-10
  • IBM Cloud Pak for Data Landing page
    Landing page //
    2023-02-11

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.

IBM Cloud Pak for Data features and specs

  • Unified Platform
    IBM Cloud Pak for Data offers a unified platform that integrates various data management tasks, including data collection, processing, governing, and analyzing. This cohesion facilitates streamlined workflows and reduces the complexity involved in managing disparate tools.
  • Scalability
    The platform is designed to scale according to business needs, from small datasets to large-scale enterprise environments. Kubernetes-based containerization allows for efficient resource allocation and scalability.
  • AI and Machine Learning Integration
    IBM Cloud Pak for Data comes with built-in AI and machine learning capabilities, enabling organizations to leverage advanced analytics and predictive modeling directly within the platform.
  • Flexible Deployment Options
    Users can deploy IBM Cloud Pak for Data across multiple environments such as on-premises, private cloud, and public cloud, offering flexibility to meet various business and regulatory requirements.
  • Security and Compliance
    The platform includes robust security features that help ensure data protection and compliance with various regulatory standards, including GDPR and CCPA.
  • Integration with Existing Systems
    IBM Cloud Pak for Data supports APIs and connectors for seamless integration with existing systems and data sources, enabling smoother data flow and reducing the need for extensive custom development.
  • Comprehensive Toolset
    The platform offers a wide range of tools for data governance, data science, data engineering, and business analytics, providing a comprehensive solution for end-to-end data management.

Possible disadvantages of IBM Cloud Pak for Data

  • Learning Curve
    Given its comprehensive and feature-rich nature, IBM Cloud Pak for Data may have a steep learning curve, particularly for users who are new to IBM products or advanced data management tools.
  • Cost
    Depending on the scale of deployment and required features, the platform can be relatively expensive, potentially making it less suitable for smaller organizations with limited budgets.
  • Complexity
    The extensive capabilities and modular architecture can introduce complexity, requiring skilled personnel for effective implementation and management.
  • Dependency on IBM Ecosystem
    Organizations that are heavily invested in non-IBM technologies might find it challenging to integrate IBM Cloud Pak for Data seamlessly with their existing ecosystem.
  • Vendor Lock-In
    There is a risk of vendor lock-in, as committing to IBM Cloud Pak for Data can make it difficult to switch to alternative solutions without significant effort and cost.
  • Hardware Requirements
    Organizations opting for on-premises deployments may face significant hardware requirements, which could necessitate additional capital investment.
  • Customization Needs
    Depending on the specific needs of the organization, substantial customization might be required to tailor the platform to fit unique business processes and workflows.

Apache Doris videos

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IBM Cloud Pak for Data videos

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IBM Cloud Pak for Data - Product Walkthrough

More videos:

  • Review - Overview of IBM Cloud Pak for Data

Category Popularity

0-100% (relative to Apache Doris and IBM Cloud Pak for Data)

Apache Doris

IBM Cloud Pak for Data

Databases
100 100%
Databases
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Relational Databases
100 100%
Relational Databases
0% 0
Data Dashboard
0 0%
Data Dashboard
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 Apache Doris and IBM Cloud Pak for Data

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

IBM Cloud Pak for Data Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
IBM Cloud Pak for Data is a fully-integrated, cloud native, data and AI platform designed for sophisticated DataOps and business analytics solutions. IBM boasts a potential for a 25-65% reduction in extract, transform, load (ETL) requests by eliminating the complexities of data integration of different data types and structures using Cloud Pak for Data. You can customize...
Source: theqalead.com

Social recommendations and mentions

Based on our record, Apache Doris seems to be more popular. It has been mentiond 6 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 (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 / 9 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 / 11 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 / 12 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 / 12 months ago
View more

IBM Cloud Pak for Data mentions (0)

We have not tracked any mentions of IBM Cloud Pak for Data yet. Tracking of IBM Cloud Pak for Data recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Doris and IBM Cloud Pak for Data, 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.

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

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.

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

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

MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

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