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Looker VS Apache Drill

Compare Looker VS Apache Drill and see what are their differences

Draxlr
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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Looker logo Looker

Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Apache Drill logo Apache Drill

Schema-Free SQL Query Engine for Hadoop and NoSQL
  • Looker Landing page
    Landing page //
    2023-10-11

Looker is a business intelligence platform with an analytics-oriented application server that sits on top of relational data stores. The Looker platform includes an end-user interface for exploring data, a reusable development paradigm for creating data discovery experiences, and an extensible API set so the data can exist in other systems. Looker enables anyone to search and explore data, build dashboards and reports, and share everything easily and quickly.

  • Apache Drill Landing page
    Landing page //
    2023-06-17

Looker features and specs

  • Powerful Data Modeling
    Looker uses LookML, a proprietary modeling language, making it possible to transform raw data into meaningful metrics and dimensions, providing deep insights without needing SQL expertise.
  • Ease of Use
    Its intuitive user interface enables non-technical users to create visualizations and reports with relative ease, reducing the workload on data teams.
  • Customization
    Looker offers extensive customization options for data exploration and visualization, allowing dashboards and reports to be tailored to specific user needs.
  • Embedded Analytics
    Provides robust capabilities for embedding analytics into applications or portals, broadening the scope of data-driven decision-making throughout the organization.
  • Real-time Data
    Supports real-time data analytics by querying live data, which ensures up-to-date insights and helps in making timely decisions.
  • Integrations
    Looker integrates seamlessly with a wide range of databases and cloud data warehouses, including Google BigQuery, Amazon Redshift, and Snowflake.

Possible disadvantages of Looker

  • Learning Curve
    LookML, while powerful, can be complex for beginners who are not already familiar with data modeling or SQL, resulting in a steep learning curve.
  • Cost
    Looker can be expensive, especially for small businesses, as pricing is typically based on the number of users and the data volume processed.
  • Performance
    Query performance can sometimes be slow, especially with complex data models and large data sets, which may impact the user experience.
  • Customization Constraints
    While Looker offers great customization, certain advanced customizations may require significant expertise and time, posing a potential barrier.
  • Limited Offline Capabilities
    Looker is primarily designed for online use, so it lacks robust offline capabilities, which can be a limitation for users who need access to data in situations without internet connectivity.

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.

Analysis of Looker

Overall verdict

  • Looker is generally considered a robust solution for organizations looking to enhance their data-driven decision-making capabilities. Its flexibility, extensibility, and ease of use make it a strong contender in the BI space, though it may require some learning and setup effort to fully utilize its features.

Why this product is good

  • Looker is a data analytics platform that provides powerful tools for data exploration, visualization, and business intelligence. It offers a user-friendly interface and is known for its ability to connect to a wide variety of data sources. Looker's LookML, a modeling language, allows users to define data relationships and calculations, making it easier to create custom reports and dashboards. Additionally, it integrates well with other tools and supports collaboration with data teams.

Recommended for

  • Companies seeking scalable and flexible business intelligence solutions.
  • Organizations that need to integrate multiple data sources.
  • Teams looking for a collaborative platform with custom reporting capabilities.
  • Users who prefer a code-based approach to data modeling and analysis.

Looker videos

+ Add

Looker Review

More videos:

  • Tutorial - How To Use Looker as a Business User
  • Review - Looker Review - Off The Shelf Reviews

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 Looker and Apache Drill)

Looker

Apache Drill

Data Dashboard
100 100%
Data Dashboard
0% 0
Databases
0 0%
Databases
100% 100
Business Intelligence
100 100%
Business Intelligence
0% 0
Relational Databases
0 0%
Relational Databases
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 Looker and Apache Drill

Looker Reviews

Explore 7 Tableau Alternatives for Data Visualization and Analysis
Looker Studio, formerly Google Data Studio, is a user-friendly business intelligence tool that transforms raw data into interactive, customizable dashboards and reports. It integrates seamlessly with Google's ecosystem and supports various data sources, including Google Analytics and BigQuery. Looker Studio offers robust visualization capabilities and real-time collaborative...
Source: www.draxlr.com
Explore 6 Metabase Alternatives for Data Visualization and Analysis
To find the best Metabase alternative for your business, start by listing your specific requirements, such as customer support, data integrations, visualization options, user access controls, and budget. Compare these needs with the features of other BI tools like Draxlr, Tableau, Power BI, Looker, or Holistics. Once you've identified a few suitable options, take advantage...
Source: www.draxlr.com
5 best Looker alternatives
In this blog, we’ll dive into the best 5 Looker alternatives currently dominating the market. Whether you're seeking a Looker alternative with enhanced features, better pricing, or a more tailored fit for your analytics needs, this guide will help you discover BI tool that could be a perfect match for your business.
Source: www.draxlr.com
10 Best Alternatives to Looker in 2024
Exploring alternatives to Looker isn't just about finding a different tool; it's about uncovering solutions that better address your specific business challenges and operational workflows. Here, we highlight five areas where Looker's limitations might lead you to consider other options.
Source: www.sigmacomputing.com
6 Best Looker alternatives
So who are Looker’s competitors? Our top 5 Looker alternatives provide data visualisation and exploration for business intelligence but also offer lower price points, less of a learning curve, and more accessibility for your non-tech team.
Source: trevor.io

Apache Drill Reviews

We have no reviews of Apache Drill yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Looker should be more popular than Apache Drill. It has been mentiond 14 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.

Looker mentions (14)

  • edit home page to add folder section
    Then in the "foldername" you can have 5 folders, each one for each of the groups. This means that when group1 enters looker.com, his default page will be the "foldername", which contains group1folder (he cannot see the rest of the folders if you have set the permissions correctly for each folder). Source: about 2 years ago
  • Stars, tables, and activities: How do we model the real world?
    Even if you want to make Wide Tables, combining fact and dimensions is often the easiest way to create them, so why not make them available? Looker, for example, is well suited to dimensional models because it takes care of the joins that can make Kimball warehouses hard to navigate for business users. - Source: dev.to / over 2 years ago
  • dbt for Data Quality Testing & Alerting at FINN
    We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / about 3 years ago
  • I'm a dev ID 10 T please help me
    Dashboard: I like to use Datastudio because it's easy (just like using google sheets), but you can also try out Looker. Source: over 3 years ago
  • The Data Stack Journey: Lessons from Architecting Stacks at Heroku and Mattermost
    For Growth and larger, I would recommend Looker. The only reason I wouldn't recommend it for the smaller company stages is that the cost is much higher than alternatives such as Metabase. With Looker, you define your data model in LookML, which Looker then uses to provide a drag-and-drop interface for end-users that enables them to build their own visualizations without needing to write SQL. This lets your... - Source: dev.to / over 3 years ago
View more

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 Looker and Apache Drill, you can also consider the following products

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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

Microsoft Power BI - BI visualization and reporting for desktop, web or mobile

Open PostgreSQL Monitoring - Oversee and Manage Your PostgreSQL Servers

Sisense - The BI & Dashboard Software to handle multiple, large data sets.

ReactiveMongo - Non-blocking, Reactive MongoDB Driver for Scala

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