Google BigQuery vs. Oracle Autonomous Database

Google BigQuery is great for being the central datastore and entry point of data if you're on GCP. It seamlessly integrates with other Google products, meaning you can ingest data from other Google products with ease and little technical knowledge, and all of it is near real-time. Being serverless, BigQuery will scale with you, which means you don't have to worry about contention or spikes in demand/storage. This can, however, mean your costs can run away quickly or mount up at short notice.

Incentivized

Scenarios where this is best suited are like where there are not large set of data which has to be analyzed and extracted.It helps in the efficiency of data .It is also well suited for medium size companies where you have to create a common data for everyone. As for large set of data, there can be network latency issues and thus there are some limitations of this software.

Incentivized

• Its serverless architecture and underlying Dremel technology are incredibly fast even on complex datasets. I can get answers to my questions almost instantly, without waiting hours for traditional data warehouses to churn through the data.
• Previously, our data was scattered across various databases and spreadsheets and getting a holistic view was pretty difficult. Google BigQuery acts as a central repository and consolidates everything in one place to join data sets and find hidden patterns.
• Running reports on our old systems used to take forever. Google BigQuery's crazy fast query speed lets us get insights from massive datasets in seconds.

Incentivized

• Robust - this product doesn't have a lot of downtime. It's less prone to errors than some other tools I've worked with.
• Scalable - we can keep adding more things to it. We haven't hit any roadblocks when we've tried to do more with our database.

Incentivized

• It is challenging to predict costs due to BigQuery's pay-per-query pricing model. User-friendly cost estimation tools, along with improved budget alerting features, could help users better manage and predict expenses.
• The BigQuery interface is less intuitive. A more user-friendly interface, enhanced documentation, and built-in tutorial systems could make BigQuery more accessible to a broader audience.

Incentivized

• There is no access to the physical host of the DB. This is expected from a managed DB. Everything must be done through the console or via API calls. This is a new learning curve for the DBAs.
• Due to the lack of physical host access, certain features are not supported, such as Transportable tablespaces and Oracle LogMiner.
• Certain special data types, (such as XMLType) are not allowed; be sure the app vendor certifies their product on this platform.

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

Autonomous is the way of the future and this is one system which is crucial to any system and is also autonomous. It is self-tuning and self-maintaining which are major advantages.

Incentivized

web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2

The product is continuously evolving and new features are added frequently. Management options through the OCI (Oracle Cloud Infrastructure) console and through the command line and API are being enhanced frequently.

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

Google BigQuery of course collects a much much larger array of raw data and can handle (practically) an unlimited amount of data. For a large enterprise like ours that relies on large-scale analytics, this is absolutely imperative. Google BigQuery can also combine GA4 data with external sources (like CRM tools), so our analytics can be unified. Due to our heavy reliance on GA4, Google BigQuery is the natural choice since it is a Google product and has better integration.

Incentivized

Hands down it's the best. It's secure and extremely fast. It also doesn't need a lot of babysitting. It's running itself. It does its job as advertised. This is why I feel everyone should if they haven't already taken a hard look OAD. I feel it's the future of technology at its best. Everyone should be taking notice of how far technology has come and where it's going.

Incentivized

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

• In some places, Google BigQuery has helped us save some money by avoiding the need for expensive infrastructure and reducing some of the operational costs.
• Scalability is up-to-date and really helpful in multiple places.
• Knowledge transfer is easy as it is very user-friendly, so the learning curve has been reduced.
• Also, it gives us more insights from our data, helping us make smarter decisions for our business.

Incentivized

• Oracle Autonomous Database has a wide range of warehouses, which is competent and of high performance.
• The transactional processing power that Oracle Autonomous Database outlines are completely important and digital.
• The efficiency of Oracle Autonomous Database data encryption fosters security measures, a form that demands more threat detectors.

Incentivized