I have used Snowflake and DataGrip for data retrieval as well as Google BigQuery and can say that all these tools compete for head to head. It is very difficult to say which is better than the other but some features provided by Google BigQuery give it an edge over the others. …
I think it blows away MySQL Workbench hands down. Workbench does have more functionality when it comes managing the MySQL instance, viewing performance etc. Navicat is ok, it might be better for new database develoopers. I stumbled upon DataGrip cause it came with jetbrains …
Easier to use, more features, more reliable. Much more purpose built with specific integrations aimed directly at php code instead of the broad generic interfaces the other software have that are aiming to support many different languages.
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Both Visual Studio Code an Sublime Text are excellent code editors, and even offer a better performance than PHPStorm. However they are not complete IDE's and do not perform half of the tasks that PHPStorm does.
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).
You will like DataGrip; it is the best software to channel and influence data systems and efficiently. It will help you be more efficient and productive in exporting computer data; it is very effective. There are no errors, and you will feel comfortable using them. It promotes data quality and has excellent graphics to represent your information through statistical processes.
PhpStorm is well suited for any project that utilizes PHP. I have used it on Windows, Ubuntu, and Mac OS and it works great on all those platforms. Having a solution that keeps the developer from having to constantly switch tools to do their job is invaluable. Whether you're a junior developer, front end engineer or a senior developer, PhpStorm is a great product that will help you get your work done.
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.
Database browsing, Remote host browsing, and all the deep seated customizations for both the UI and Technical feasability are the result of an amazing integrity and compatibility with most components and technologies.
The built-in shell is insanely helpful for traversing code in order to debug scripts with ease, and the plug-in system makes this software quite extensible.
Not to mention the variety of options and settings (divided into global settings and per-project settings) are both intuitive & easy to use, especially the fact that I can export and import them across my workstations while maintaining my spacing & indentation, highlighting, inspection patterns and syntax styling.
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.
Some of the newest github copilot features lag behind what's being done in vs code and would be nice if more of the newer features were brought over though this has greatly improved recently
Interface can be a little overwhelming for newcomers
Some features like rainbow brackets should be native rather than addon
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.
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.
Usability has two aspects, being a complete tool and being easy... DataGrip has a lot of features but it is big, not clear how to use most of the things and most people won't need them. In my opinion, usability is good enough but not friendly.
PhpStorm is very easy to use, once you get the hang of it. It can take a while to get the hang of it because there's so many options, some of which are buried in the imposing settings panel. It could use some help with multi-cursor, especially multi-file editing but that's a minor gripe.
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.
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.
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.
The JetBrains community is all about helping others succeed, even in the most obscure setups. I have never had a question go unanswered, or I have never been able to come up with empty results in searching for the answer. My questions or concerns are typically address from other users in the community, so timing is pretty quick for a response
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.
DataGrip provides a single UI for many DBMS platforms, instead of using one for each. Because of that, you can migrate things between platforms using the tool and "look across" all databases at once.
Easier to use, more features, more reliable. Much more purpose built with specific integrations aimed directly at php code instead of the broad generic interfaces the other software have that are aiming to support many different languages.
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.
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.
PhpStorm decreased the time to market of new features - we are following the Agile SCRUM methodology with 2 weeks sprints. Using PhpStorm helped with releasing UI features even faster than 2 weeks.
Considering the price of the license and the cost of the server where we run it, the ROI is still high due to less time spent by developers with writing code, debugging, refactoring etc. Especially when you have highly paid developers.
Increased people's happiness - by using a modern tool with lots of features which has made their work easier.
