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Open Data Hub VS Apache Drill

Compare Open Data Hub VS Apache Drill and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Open Data Hub logo Open Data Hub

OpenDataHub

Apache Drill logo Apache Drill

Schema-Free SQL Query Engine for Hadoop and NoSQL
  • Open Data Hub Landing page
    Landing page //
    2023-06-01
  • Apache Drill Landing page
    Landing page //
    2023-06-17

Open Data Hub features and specs

No features have been listed yet.

Apache Drill features and specs

  • Schema-Free JSON Querying
    Apache Drill is designed to handle schema-less data, allowing users to query JSON and other flexible schemas without needing pre-defined structures. This flexibility makes it ideal for exploring semi-structured data on the fly.
  • SQL Interface
    Drill offers a user-friendly SQL interface, making it accessible for users familiar with traditional SQL databases. This allows professionals to leverage their existing SQL skills to interact with big data ecosystems.
  • High Performance
    With its ability to efficiently process queries on large datasets, Apache Drill is optimized for high-performance analytics and interactive queries, making it suitable for rapid insights and data exploration.
  • Integration with Multiple Data Sources
    Apache Drill can natively connect to a wide variety of data sources, including Hadoop, NoSQL databases, and cloud storage systems. This integration provides a unified view of diverse datasets without extensive ETL processes.
  • Dynamic Query Optimization
    Drill performs on-the-fly query optimization based on the available data and resource conditions, helping ensure efficient query execution and reduced latency.

Possible disadvantages of Apache Drill

  • Memory Intensive
    Apache Drill can be memory-intensive, especially when handling complex queries or very large datasets. This requires substantial hardware resources for optimal performance, which can be cost-prohibitive.
  • Lack of Mature Support and Community
    Compared to some other open-source projects, Apache Drill does not have as extensive a support network or community. This can make troubleshooting and finding community-driven solutions more challenging.
  • Limited Built-in Security Features
    While Apache Drill supports authentication and encryption, it lacks more granular access controls and advanced security features found in some competing platforms, posing potential risks in highly regulated environments.
  • Steep Learning Curve for Modifications
    For users wanting to extend or modify Apache Drill's capabilities beyond its core functions, the learning curve can be steep due to its architecture and the need for in-depth technical knowledge.
  • Updates and Active Development
    Although Apache Drill is actively developed, the pace of updates may not be as rapid or extensive as newer systems, which might delay the adoption of the latest data processing features and technologies.

Open Data Hub videos

+ Add

Open Data Hub Introduction

More videos:

  • Review - Fraud Detection Using Open Data Hub on Openshift
  • Review - Installing Open Data Hub on OpenShift 4.1

Apache Drill videos

+ Add

Using Apache Drill

More videos:

  • Review - Drilling into Data with Apache Drill
  • Review - Apache Drill and the Coolness of Big JSON - Jonathan Janos (MapR)

Category Popularity

0-100% (relative to Open Data Hub and Apache Drill)

Open Data Hub

Apache Drill

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Databases
0 0%
Databases
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Database Management
0 0%
Database Management
100% 100

User comments

Share your experience with using Open Data Hub and Apache Drill. For example, how are they different and which one is better?
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Social recommendations and mentions

Apache Drill might be a bit more popular than Open Data Hub. We know about 3 links to it since March 2021 and only 3 links to Open Data Hub. 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.

Open Data Hub mentions (3)

  • job scheduling for scientific computing on k8s?
    Perhaps have a look at OpenDataHub. While geared for Openshift, see if they solved some of your concerns. Source: almost 2 years ago
  • Elyra 2.2: R support, updated CLI, and more
    A common approach is to deploy JupyterHub on Kubernetes and configure it for Elyra, like it is done in Open Data Hub on the Red Hat OpenShift Container platform. - Source: dev.to / over 4 years ago
  • Automate your machine learning workflow tasks using Elyra and Apache Airflow
    If you are interested in running pipelines on Apache Airflow on the Red Hat OpenShift Container Platform, take a look at Open Data Hub. Open Data Hub is an open source project (just like Elyra) that should include everything you need to start running machine learning workloads in a Kubernetes environment. - Source: dev.to / over 4 years ago

Apache Drill mentions (3)

  • Git Query Language (GQL) Aggregation Functions, Groups, Alias
    Also are you familiar with apache drill . The idea is to put an SQL interpreter in front of any kind of database just like you are doing for git here. Source: almost 2 years ago
  • Roapi: An API Server for Static Datasets
    Looks super interesting and potentially useful. Curious how it compares with Apache Drill (https://drill.apache.org/). - Source: Hacker News / over 3 years ago
  • Does Java have an open source package that can execute SQL on txt/csv?
    Check out Apache Drill: https://drill.apache.org/. Source: over 3 years ago

What are some alternatives?

When comparing Open Data Hub and Apache Drill, you can also consider the following products

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

Apache Calcite - Relational Databases

Open PostgreSQL Monitoring - Oversee and Manage Your PostgreSQL Servers

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

ReactiveMongo - Non-blocking, Reactive MongoDB Driver for Scala

C3 AI Suite - The C3 AI Suite uses a model-driven architecture to accelerate delivery and reduce the complexities of developing enterprise-scale AI applications.

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