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)
Oracle SQL Developer
Score 7.9 out of 10
N/A
Oracle SQL Developer is an integrated development environment (IDE) which provides editors for working with SQL, PL/SQL, Stored Java Procedures, and XML in Oracle databases.
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Pricing
Google BigQuery
Oracle SQL Developer
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
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Offerings
Pricing Offerings
Google BigQuery
Oracle SQL Developer
Free Trial
Yes
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Community Pulse
Google BigQuery
Oracle SQL Developer
Features
Google BigQuery
Oracle SQL Developer
Database-as-a-Service
Comparison of Database-as-a-Service 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).
Almost all development activities (the tool is called "SQL Developer", not "DBA Toolset") can be done easily and quick with [Oracle] SQL Developer. From data model creation (tables, views) to development (creation of procedures, functions, packages) and then testing (SQL Developer includes an easy to use debugger), all tasks can be performed in a single tool.
It may not be as complete as other solutions for DBA tasks like instance monitoring, but it is usually OK for development and testing environments if you want to do some basic troubleshooting.
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.
Object Browser in SQL Developer allows you to explore the contents of your database using the connection tree.
The SQL Worksheet is an editor that allows for execution of SQL statements, scripts, and PL/SQL anonymous blocks. SELECT statements can be executed to return results in a spreadsheet-like 'grid' or can be executed as a script such to emulate SQL*Plus behavior and output
DBA Console allows users with administrative privileges to access DBA features such as database init file configuration, RMAN backup, storage, etc.
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.
Inability to run multiple queries on the same database. You can only run one query on a given database.
Analytical models created from complex tables isn't accurate, and needs work.
Inability to view multiple tables of a database side-by-side. When trying to find correlations between tables, it would help to be able to see them at once on the same page.
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.
Oracle SQL Developer is very easy to use and there are a wide range of courses available which can help you get started just within a day. Data can be exported in multiple formats based on user requirements. Organizational data can be stored and management effectively using Oracle SQL Developer. All the data, tables, sequences, indexes can be easily created and updated in Oracle SQL Developer.
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.
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.
I have started to use Toad for Oracle recently because it is easier to sort and filter results, due to their memory sort feature that puts the results from your query in memory so that you don't have to rerun your query. I have used SQL Developer to easily update records in tables that I need to fix. I haven't found an easy way to do this in Toad other than writing SQL insert statements.
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.