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Google BigQuery VS MariaDB

Compare Google BigQuery VS MariaDB and see what are their differences

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Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.

MariaDB logo MariaDB

An enhanced, drop-in replacement for MySQL
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • MariaDB Landing page
    Landing page //
    2023-04-18

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.

MariaDB features and specs

  • Open Source
    MariaDB is fully open-source, which means it is free to use, modify, and distribute. There are no licensing fees, making it a cost-effective solution for businesses of all sizes.
  • Compatibility with MySQL
    MariaDB is designed as a drop-in replacement for MySQL. It offers extensive compatibility, making it easy to switch from MySQL without needing to make significant changes to the codebase.
  • Performance
    MariaDB often offers better performance and scalability compared to other relational databases. It includes enhancements in query optimization and indexing, which can lead to faster data retrieval.
  • Advanced Features
    MariaDB includes advanced features such as the Aria storage engine, dynamic columns, and thread pooling. These features provide more flexibility and control over database management and optimization.
  • Active Community
    Being open-source, MariaDB benefits from a robust and active community of developers and users who contribute to its development and provide support through forums and other channels.
  • Security
    MariaDB is known for its strong focus on security. It includes advanced security features such as data encryption, role-based access control, and protection against SQL injection attacks.

Possible disadvantages of MariaDB

  • Learning Curve
    For new users, especially those without much experience with relational databases or MySQL, MariaDB can have a steep learning curve. It requires an understanding of SQL, database management, and various configurations.
  • Inconsistent Documentation
    While the community is active, the documentation can sometimes be inconsistent or incomplete. This can make troubleshooting and leveraging advanced features more challenging.
  • Compatibility Issues
    Although MariaDB aims to be compatible with MySQL, certain features or configurations might not work identically, leading to potential compatibility issues with some applications.
  • Fewer Enterprise Features
    Compared to commercial database solutions like Oracle, MariaDB may lack certain enterprise-level features, tools, and support options that large corporations might require.
  • Market Adoption
    MariaDB, while popular, does not have as wide of an adoption as MySQL or other big players in the database market, which can be a consideration for integration and support in some environments.

Analysis of Google BigQuery

Overall verdict

  • Google BigQuery is a powerful and flexible data warehouse solution that suits a wide range of data analytics needs. Its ability to handle large volumes of data quickly makes it a preferred choice for organizations looking to leverage their data effectively.

Why this product is good

  • Google BigQuery is a fully-managed data warehouse that simplifies the analysis of large datasets. It is known for its scalability, speed, and integration with other Google Cloud services. It supports standard SQL, has built-in machine learning capabilities, and allows for seamless data integration from various sources. The serverless architecture means that users don't need to worry about infrastructure management, and its pay-as-you-go model provides cost efficiency.

Recommended for

  • Businesses requiring fast processing of large datasets
  • Organizations that already utilize Google Cloud services
  • Companies looking for a cost-effective, scalable analytics solution
  • Teams interested in using SQL for data analysis
  • Data scientists integrating machine learning with their data workflows

Analysis of MariaDB

Overall verdict

  • MariaDB is generally considered a good and reliable choice for database management, offering a strong feature set, active development community, and favorable performance.

Why this product is good

  • MariaDB is a popular fork of MySQL, known for being open-source and community-driven.
  • It offers enhanced performance and scalability, often outperforming MySQL in benchmark tests.
  • MariaDB includes features not present in MySQL, such as the Aria storage engine and better support for JSON.
  • Developed by the original creators of MySQL, ensuring continuity in quality and development philosophy.

Recommended for

  • Organizations looking for a robust, open-source alternative to MySQL.
  • Developers wanting to avoid the commercial restrictions of MySQL due to Oracle's ownership.
  • Projects that require high-performance, scalable database management systems.
  • Users looking for additional features and storage engines not available in MySQL.

Google BigQuery videos

+ Add

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

MariaDB videos

+ Add

MySQL/MariaDB Basics (RHCE Study)

More videos:

  • Review - MariaDB Storage Engines
  • Tutorial - #MariaDB Server 10.2: The Complete Guide - #Database Tutorial

Category Popularity

0-100% (relative to Google BigQuery and MariaDB)

Google BigQuery

MariaDB

Data Dashboard
100 100%
Data Dashboard
0% 0
Databases
0 0%
Databases
100% 100
Big Data
100 100%
Big Data
0% 0
NoSQL Databases
0 0%
NoSQL 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 Google BigQuery and MariaDB

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

MariaDB Reviews

Data Warehouse Tools
MariaDB is another open-source relational database management system that can be used for data warehousing. It’s a robust and secure option for organizations seeking a familiar and cost-effective solution, especially those already invested in the MySQL ecosystem.
Source: peliqan.io
MariaDB Vs MySQL In 2019: Compatibility, Performance, And Syntax
Even the command line tools are similar to mysqldump and mysqladmin still having the original names, allowing MariaDB to be a drop-in replacement.To make sure MariaDB maintains drop-in compatibility, the MariaDB developers do a monthly merge of the MariaDB code with the MySQL code. Even with this, there are some differences between MariaDB and MySQL that could cause some...
Source: blog.panoply.io

Social recommendations and mentions

MariaDB might be a bit more popular than Google BigQuery. We know about 43 links to it since March 2021 and only 42 links to Google BigQuery. 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.

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 / 5 months 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 / 6 months 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 / 6 months ago
  • Study Notes 2.2.7: Managing Schedules and Backfills with BigQuery in Kestra
    BigQuery Documentation: Google Cloud BigQuery. - Source: dev.to / 8 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 / 11 months ago
View more

MariaDB mentions (43)

  • Integrating MongoDB into Laravel with Filament
    Laravel is one of the best PHP frameworks I ever tried in my career which works very well with relational databases such MariaDB or PostgreSQL. However recently I had the opportunity to dig into NoSQL databases, specifically into MongoDB that offers amazing features like TTL indexes or embedded documents (aka One to Few relationships). - Source: dev.to / 11 days ago
  • OpenBSD Upgrade 7.6 to 7.7
    In addition, it also includes MariaDB update where "Binary logs are no longer purged by default unless a replica has connected", and minio update where "the MinIO Gateway and the related filesystem mode code have been removed". - Source: dev.to / 5 months ago
  • MariaDB (Bite-size Article)
    Download from the Official Website: Visit the official MariaDB website (https://mariadb.org/) and download the version that matches your operating system. - Source: dev.to / 10 months ago
  • From License to Freedom: Embracing Open Source Forks Knowing What to Expect
    One of the most famous examples is MariaDB, a fork of MySQL. When Oracle acquired MySQL back in 2009, concerns arose about the future of the database under a corporate umbrella and while MySQL has remained open source, the idea of it living under Oracle's roof was enough to push some of the original creators to fork an alternative that still lived within the developer community. During the early stages of MariaDB,... - Source: dev.to / 11 months ago
  • Using the built-in SQLite module in Node.js
    SQLite is a lightweight database engine written in C. It is a simple, fast, and fully featured implementation of an SQL Database Management System. SQLite differs from other relational databases like MariaDB and PostgreSQL because it does not run as a server. - Source: dev.to / 12 months ago
View more

What are some alternatives?

When comparing Google BigQuery and MariaDB, you can also consider the following products

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

MySQL - The world's most popular open source database

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.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

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

Microsoft SQL - Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.

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