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 GoldenGate
Score 8.1 out of 10
N/A
Oracle Cloud Infrastructure (OCI) GoldenGate is a managed service providing a real-time data mesh platform, which uses replication to keep data highly available, and enabling real-time analysis.
$250
Per License
Pricing
Google BigQuery
Oracle GoldenGate
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
Data Integration
$250.00
Per License
Offerings
Pricing Offerings
Google BigQuery
Oracle GoldenGate
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Google BigQuery
Oracle GoldenGate
Features
Google BigQuery
Oracle GoldenGate
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).
I think it's a great product. We apply Oracle GoldenGate to several use cases in our organization. 1. Business Continuity Planning, 2. Query Offloading through data replication to a reporting instance of our data, 3. looking into data transformations to help support various queries for different teams within the business.
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.
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.
Once set up, it's very easy to use and keep running, it's getting to that point that can make it cumbersome to some. Also, depending on the data that you want to replicate, the configuration files can become quite cumbersome to maintain. Learning curve can be high for some who are not as experienced with databases and transactions.
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.
Oracle Support for Oracle GoldenGate has been quite responsive and quite helpful in the few situations where we've needed it. Furthermore, the documentation on Oracle GoldenGate is so good that we often do not need to contact support with issues as the fix is already documented and able to be run by us without needing to open a ticket.
We've had Oracle consultants come as well for training days to talk about new features, parts of Oracle GoldenGate we may not be using and things of that nature. The consultants they send are great as they're very knowledgeable about all things Oracle GoldenGate and great resources for any questions or concerns you may have with the product.
We used Oracle University for our Oracle Golden Gate Training and it was top notch. We were able to turn our whole DBA team to Oracle GoldenGate newbies to Oracle GoldenGate troubleshooting experts in a matter of a few days, while this obviously did not come cheap, the company felt that it was worth the investment.
If Oracle GoldenGate is new to your organization, expose as many DBAs as possible to it. Having your whole team fluent in it will overcome early operational hurdles and allow it to more quickly become an accepted and supported part of your supported platform for your team that will enable the business to use it to its fullest.
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.
We use Oracle Data Guard as a backup tool, but not for data replication. Data Guard is not suited for real-time data replication in our non-normalized reporting database nor for the database we are using for our upgrade project, as Data Guard is not able to transform data and is not able to synchronize data into different schemas, which is necessary for our project. Additionally, our project database is on Oracle 12g not 11i: I am not 100% sure Data Guard is able to replicate from 11i to 12g
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.
Have never had any issues with scaling Oracle GoldenGate itself, however Oracle GoldenGate Monitor does have scaling issues, but with Oracle GoldenGate now able to be monitored by Oracle Enterprise Manager, this is no longer an issue, in my opinion.
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.
In earlier versions, DDL support was limited as well as the need of primary key constraints in the source tables. This made me create partitions, sub-partitions, truncatations and perform other operations upon they are performed in source systems and I need to discuss with source system administrators and need to convince them to let them create primary keys for replicated tables.
But both issues are solved now.
Installation is straightforward, easy.
Deployed everything within Oracle Data Integrator.
Developing 1000 of ODI interfaces for loading into Operational Data Store took not more than 100 man/days. But, adding them to Golden Gate is taking not more than 5 man/days.
Management Pack and VeriData are additional packs for your management and data verification needs.
