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Apache HTTP Server VS Google BigQuery

Compare Apache HTTP Server VS Google BigQuery and see what are their differences

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Apache HTTP Server logo Apache HTTP Server

Apache httpd has been the most popular web server on the Internet since April 1996

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • Apache HTTP Server Landing page
    Landing page //
    2021-10-21
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

Apache HTTP Server features and specs

  • Open Source
    Apache HTTP Server is open source, meaning it is freely available for anyone to use, modify, and distribute. This promotes a large, active community that contributes to its maintenance and improvement.
  • Cross-Platform
    Apache is compatible with a variety of operating systems, including Unix, Linux, and Windows, providing flexibility and widespread usability.
  • Highly Customizable
    It offers a modular architecture that allows users to enable or disable features as needed, and to extend functionality through modules.
  • Robust Documentation
    Apache provides comprehensive and detailed documentation, which makes it easier for users to install, configure, and troubleshoot the server.
  • Widespread Adoption
    With its long history and widespread use, Apache has proven to be reliable and trusted by many organizations worldwide, ensuring a level of trust and stability.
  • Rich Feature Set
    Apache includes many features out-of-the-box, such as SSL/TLS support, URL redirection, authentication, load balancing, and more.

Possible disadvantages of Apache HTTP Server

  • Performance Overhead
    Compared to some lightweight web servers like Nginx, Apache can have higher memory and CPU usage, which may not be ideal for high concurrency needs.
  • Complex Configuration
    Apache's extensive customization options can lead to a complex configuration process, which may be challenging for beginners or those without specific expertise.
  • Less Efficient in Serving Static Content
    While Apache is highly capable, it may be less efficient at serving static content compared to specialized web servers like Nginx.
  • Initial Learning Curve
    Due to its rich features and configurability, new users might face a steep learning curve when first setting up and using Apache HTTP Server.
  • Module Compatibility Issues
    Sometimes, third-party modules may not always be compatible with the latest versions of Apache, causing potential integration issues.

Google BigQuery features and specs

  • Scalability
    BigQuery can effortlessly scale to handle large volumes of data due to its serverless architecture, thereby reducing the operational overhead of managing infrastructure.
  • Speed
    It leverages Google's infrastructure to provide high-speed data processing, making it possible to run complex queries on massive datasets in a matter of seconds.
  • Integrations
    BigQuery easily integrates with various Google Cloud Platform services, as well as other popular data tools like Looker, Tableau, and Power BI.
  • Automatic Optimization
    Features like automatic data partitioning and clustering help to optimize query performance without requiring manual tuning.
  • Security
    BigQuery provides robust security features including IAM roles, customer-managed encryption keys, and detailed audit logging.
  • Cost Efficiency
    The pricing model is based on the amount of data processed, which can be cost-effective for many use cases when compared to traditional data warehouses.
  • Managed Service
    Being fully managed, BigQuery takes care of database administration tasks such as scaling, backups, and patch management, allowing users to focus on their data and queries.

Possible disadvantages of Google BigQuery

  • Cost Predictability
    While the pay-per-use model can be cost-efficient, it can also make cost forecasting difficult. Unexpected large queries could lead to higher-than-anticipated costs.
  • Complexity
    The learning curve can be steep for those who are not already familiar with SQL or Google Cloud Platform, potentially requiring training and education.
  • Limited Updates
    BigQuery is optimized for read-heavy operations, and it can be less efficient for scenarios that require frequent updates or deletions of data.
  • Query Pricing
    Costs are based on the amount of data processed by each query, which may not be suitable for use cases that require frequent analysis of large datasets.
  • Data Transfer Costs
    While internal data movement within Google Cloud can be cost-effective, transferring data to or from other services or on-premises systems can incur additional costs.
  • Dependency on Google Cloud
    Organizations heavily invested in multi-cloud or hybrid-cloud strategies may find the dependency on Google Cloud limiting.
  • Cold Data Performance
    Query performance might be slower for so-called 'cold data,' or data that has not been queried recently, affecting the responsiveness for some workloads.

Apache HTTP Server videos

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Google BigQuery videos

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Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

Category Popularity

0-100% (relative to Apache HTTP Server and Google BigQuery)

Apache HTTP Server

Google BigQuery

Web And Application Servers
100 100%
Web And Application Servers
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Web Servers
100 100%
Web Servers
0% 0
Big Data
0 0%
Big Data
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 HTTP Server and Google BigQuery

Apache HTTP Server Reviews

9 Best XAMPP Alternatives Cross Platform Web Server
However, compared to XAMPP and other popular web servers in the market Apache HTTP Server is a bit more complicated and is a little difficult to navigate for a complete newbie, but if you want to understand web development from the very fundamentals and understand how Apache as a web server software works then this software can be of great help to you.
Source: technicalustad.com
Litespeed vs Nginx vs Apache: Web Server Showdown
The most commonly used Web Server is by far Apache HTTP Server from the Software Apache Foundation. Created in 1995 by Rob McCool and Brian Behlendorf, among others. The name is a pun for A PatCHy server, as at the time of it’s inception, Apache was based on some existing code, along with some perhaps “hacky or clunky” software packages, enabling it to run. Additionally, the...
Source: chemicloud.com
10 Best alternatives of XAMPP servers for Windows, Linux and macOS
Apache is an open-source and free web server software that owns about 46% of websites worldwide. The official name is Apache HTTP Server and is maintained and developed by the Apache Software Foundation. This allows website owners to serve content on the web – hence the name “webserver”.
Source: www.isrgrajan.com
Top 5 open source web servers
As the Apache HTTP Server has been the most popular web server since 1996, it "benefits from great documentation and integrated support from other software projects." You can find more information on the Apache Foundation project page.
Source: opensource.com

Google BigQuery Reviews

Data Warehouse Tools
Google BigQuery: Similar to Snowflake, BigQuery offers a pay-per-use model with separate charges for storage and queries. Storage costs start around $0.01 per GB per month, while on-demand queries are billed at $5 per TB processed.
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
You can also use BigQuery’s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Google BigQuery is an incredible platform for enterprises that want to run complex analytical queries or “heavy” queries that operate using a large set of data. This means it’s not ideal for running queries that are doing simple filtering or aggregation. So if your cloud data warehousing needs lightning-fast performance on a big set of data, Google BigQuery might be a great...
Source: www.shipyardapp.com
Top 5 BigQuery Alternatives: A Challenge of Complexity
BigQuery's emergence as an attractive analytics and data warehouse platform was a significant win, helping to drive a 45% increase in Google Cloud revenue in the last quarter. The company plans to maintain this momentum by focusing on a multi-cloud future where BigQuery advances the cause of democratized analytics.
Source: blog.panoply.io
16 Top Big Data Analytics Tools You Should Know About
Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities.
Source: www.analytixlabs.co.in

Social recommendations and mentions

Based on our record, Apache HTTP Server should be more popular than Google BigQuery. It has been mentiond 66 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 HTTP Server mentions (66)

  • Unveiling GNU Free Documentation License 1.3: A Comprehensive Exploration of Its Depths, Applications, and Future Trends
    Example: Various technical documentation projects on platforms like Apache HTTP Server have implemented GFDL clauses to safeguard documentation integrity. - Source: dev.to / 3 days ago
  • Open Source: A Goldmine for Indie Hackers
    Open source software is built on the democratic idea that everyone should be able to inspect and contribute to the source code. Major projects like Linux, WordPress, and the Apache HTTP Server have shown how collaborative efforts can produce robust, scalable solutions. Indie hackers, often working with limited budgets, gain access to highly dependable tools such as Python and MySQL, which were originally developed... - Source: dev.to / 9 days ago
  • Unveiling a Licensing Legend: The Netscape Public License 1.1
    The Netscape Public License 1.1 served as a crucial stepping stone for modern open source licensing models. Developed by Netscape Communications Corporation, it was designed to encourage global community collaboration while safeguarding intellectual property. During the rise of the open source movement, the license provided a much-needed balance between transparency and control, making it a frequent subject of... - Source: dev.to / about 2 months ago
  • Unveiling GNU FDL 1.2: A Deep Dive into Free Documentation Licensing
    Adoption, Use Cases, and Comparative Analysis: Projects ranging from community manuals to major software endeavors like the Apache HTTP Server have adopted the GNU FDL 1.2 to preserve the spirit of open documentation. While its copyleft nature ensures that every modification remains free, critics argue that the rigidity of the license may deter commercial integration. This is contrasted with alternative licensing... - Source: dev.to / about 2 months ago
  • Unveiling GNU FDL 1.1: A Deep Dive into Free Documentation Licensing
    GNU FDL 1.1 was created by the Free Software Foundation (FSF) with the intent of bringing the same freedoms found in free software to documentation. Many notable projects, including those under the aegis of the Apache HTTP Server, have benefited from a documentation license that guarantees continued openness and proper attribution. Throughout our exploration, we will delve into the evolution, strengths, and... - Source: dev.to / about 2 months ago
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Google BigQuery mentions (42)

  • Every Database Will Support Iceberg — Here's Why
    This isn’t hypothetical. It’s already happening. Snowflake supports reading and writing Iceberg. Databricks added Iceberg interoperability via Unity Catalog. Redshift and BigQuery are working toward it. - Source: dev.to / 23 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    Many of these companies first tried achieving real-time results with batch systems like Snowflake or BigQuery. But they quickly found that even five-minute batch intervals weren't fast enough for today's event-driven needs. They turn to RisingWave for its simplicity, low operational burden, and easy integration with their existing PostgreSQL-based infrastructure. - Source: dev.to / 28 days ago
  • How to Pitch Your Boss to Adopt Apache Iceberg?
    If your team is managing large volumes of historical data using platforms like Snowflake, Amazon Redshift, or Google BigQuery, you’ve probably noticed a shift happening in the data engineering world. A new generation of data infrastructure is forming — one that prioritizes openness, interoperability, and cost-efficiency. At the center of that shift is Apache Iceberg. - Source: dev.to / about 1 month ago
  • Study Notes 2.2.7: Managing Schedules and Backfills with BigQuery in Kestra
    BigQuery Documentation: Google Cloud BigQuery. - Source: dev.to / 3 months ago
  • Docker vs. Kubernetes: Which Is Right for Your DevOps Pipeline?
    Pro Tip: Use Kubernetes operators to extend its functionality for specific cloud services like AWS RDS or GCP BigQuery. - Source: dev.to / 6 months ago
View more

What are some alternatives?

When comparing Apache HTTP Server and Google BigQuery, you can also consider the following products

Microsoft IIS - Internet Information Services is a web server for Microsoft Windows

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Apache Tomcat - An open source software implementation of the Java Servlet and JavaServer Pages technologies

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.

LiteSpeed Web Server - LiteSpeed Web Server (LSWS) is a high-performance Apache drop-in replacement.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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