Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Microsoft Access
Score 7.5 out of 10
N/A
Microsoft Access is a database management system from Microsoft that combines the relational Microsoft Jet Database Engine with a graphical user interface and software-development tools.
At my previous organization we used server based SQL server. There were days when the server was down and we couldn't work or access the data. This caused multiple reports and processes which were fed from the server to fail. Google BigQuery doesn't have such problems.
Microsoft Access
No answer on this topic
Features
Google BigQuery
Microsoft Access
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google BigQuery
8.5
80 Ratings
0% below category average
Microsoft Access
-
Ratings
Automatic software patching
8.017 Ratings
00 Ratings
Database scalability
9.179 Ratings
00 Ratings
Automated backups
8.524 Ratings
00 Ratings
Database security provisions
8.773 Ratings
00 Ratings
Monitoring and metrics
8.475 Ratings
00 Ratings
Automatic host deployment
8.013 Ratings
00 Ratings
Relational Databases
Comparison of Relational Databases features of Product A and Product B
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).
As a Material Purchasing/Planning/inventory tracking application, Microsoft Access serves its purpose well. It's presentation is clean, data entry is simple and the ability to customize search fields is welcome. It does, however, come with some caveats; namely, when setting search filters and the need arises to back up a step or two, with Microsoft Access you have to reset, or "clear all", adding extra steps/time to a query.
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.
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.
Microsoft Access has not really changed at all for several years. It might be nice to see some upgrades and changes.
The help info is often not helpful. Need more tutorials for Microsoft Access to show how to do specific things.
Be careful naming objects such as tables, forms, etc. Names that are too long can get cut off in dialog boxes to choose a table, form, report, etc. So, I wish they would have resizable dialog boxes to allow you to see objects with long names.
I wish it could show me objects that are not in use in the database for current queries, tables, reports, forms, and macros. That way unused objects can be deleted without worrying about losing a report or query because you deleted the underlying object.
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 and the rest of my team will renew our Microsoft Access in the future because we use and maintain many different applications and databases created using Microsoft Access so we will need to maintain them in the future. Additionally, it is a standard at our place of work so it is at $0 cost to us to use. Another reason for renewing Microsoft Access is that we just don' t have the resources needed to extend into a network of users so we need to remain a single-desktop application at this time.
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.
Microsoft Access is easy to use. It is compatible with spreadsheets. It is a very good data management tool. There is scope to save a large amount of data in one place. For using this database, one does not need much training, can be shared among multiple users. This database has to sort and filtering features which seem to be very useful.
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.
While I have never contacted Microsoft directly for product support, for some reason there's a real prejudice against MS Access among most IT support professionals. They are usually discouraging when it comes to using MS Access. Most of this is due to their lack of understanding of MS Access and how it can improve one's productivity. If Microsoft invested more resources towards enhancing and promoting the use of MS Access then maybe things would be different.
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.
Excel is a fantastic - robust application that can do so much so easily. Its easy to train and understand. However - excel does not provide a reporting function and that is typically where we will suggest a move to [Microsoft] Access. [Microsoft] Access requires a little more knowledge of data manipulation.
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.