Google BigQuery vs. MariaDB Platform

Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).

Incentivized

• Applications where the users need [to] execute many short queries.
• With new storage engines such as Aria, which allows to replace MyISAM with some improvements, and XtraDB, which evolves InnoDB.
• To fuse the legacy features with the features available in NoSQL databases.
• Connection management, which allows multiplying the number of concurrent accesses.
• New clustering engines, such as Galera, which allow interesting possibilities for Cloud adoption.

Incentivized

• Realtime integration with Google Sheets.
• GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
• Seamless integration with other GCP products.
• A simple pipeline might look like this:-
• GForms -> GSheets -> BigQuery -> Looker
• It all links up really well and with ease.
• One instance holds many projects.
• Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.

Incentivized

• Simpler learning curve. MariaDB is a cleaner, simpler system that is (IMO) easier to learn and easier to manage effectively than many other database systems.
• Lower hardware requirements. After migrating to MariaDB from another database software system, we find that our hardware needs have substantially decreased.
• MariaDB support is very responsive. It's like they actually care. On the few occasions we've run into technical issues, support has always come through with what we needed. Once it was showing me a relatively new feature the server supported that I wasn't aware of, that, once I was able to properly make use of it helped me resolve a serious production performance issue.
• Architectural flexibility. As an example, the ready availability of synchronous (Galera) versus asynchronous replication schemes without being locked into one of the other by enormous technical complexity or punitive licensing, allows the customer to find what really works best for their needs.

Incentivized

• Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
• If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
• It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.

Incentivized

• Driver Support - Some third party applications use database drivers that cause unexplained slowness with MariaDB. This can be worked around by using the MySQL drivers, but it's not clear what causes the problem in the first place.
• Support - While online communities are helpful in diagnosing problems, there isn't as much professional documentation/support available for MariaDB as some of the other major database options.
• Data Visualization - It would be helpful if there were more built in options for analyzing statistics and generating reports.

Incentivized

We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.

Incentivized

I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.

Incentivized

MariaDB is very usable and stable to be used in production settings as an alternative to MySQL. The shortcomings of SQL are present but well understood in the community, and if the decision were to be made again, I would choose MariaDB over MySQL on future projects.

Incentivized

I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.

Incentivized

I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.

Incentivized

BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.

Incentivized

We have launched several inquiries to MariaDB support and they have always responded very quickly and have not been tutoring for the duration of the incident/problem.

Likewise, they want to hold constant meetings with the client to get their opinion as well as how they can help.

I see a very human support and concerned about the customer.

Incentivized

PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.

Incentivized

MariaDB stacks up the the competition just fine. Due to is ture open source nature we do not have to worry about licencing and spending money on nothing. Moreover, MariaDB does everything that we need to get done. We can run data that is a million rows or many smaller projects on the same environment with little overhead. One of the best features that MariaDB has is the ability of backup or dump data to standard text sql statements. That was one of the reasons why we choose MariaDb because it makes backups or transferring data a snap

Incentivized

None so far. Very satisfied with the transparency on contract terms and pricing model.

We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.

Incentivized

Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.

• Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
• We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
• Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.

Incentivized

• Low CAPEX if you have a team that use open source software day by day
• Medium OPEX if you have a team that use open source software day by day
• Perfect to use in academic ambient to support researchers and students

Incentivized