Google Cloud Bigtable vs. Oracle Autonomous Database

It works great for any use case that requires high throughput for reads and writes, for key-value kinda data. This enables you to use it for usecases where you need to retain data for a long term or even short term but then use it in pipelines to enrich data, sync states between backend and frontend or to quickly lookup say a user.

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Pro - Stability. Does everything anyone could need. If it's not there it will be on the next update. There is plenty of support for it. It's been around for a long time and it's reliable. The support is well documented and has a great reputation. Cons - Errors have been found in the documentation provided by Oracle with guidelines, etc. Oracles salespeople have a reputation of being obnoxious and condescending.

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• Analytics: is at Google's heart. No on can beat Google in this space and BigTable is one of its implementation of this. The insights you gain from BigTable are simply usable in your day to day activities and can help you make real difference.
• Speed: Processing TBs and PBs of data under minutes needs real efficient platform which is capable of doing much more than just processing data. All this data cannot be processed by a single machine, but rather huge pairs of machines working in conjuction with each other. BigTable's implementation is one of the finest and allows you achieve great speeds!
• Interface: is great. Google has segregated required task under logically placed buttons which takes no time by users to understand and get habituated.

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• 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.

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• Global replication
• Complete SQL support
• Size limit of 1MB

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• 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.

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Because it does exactly what we need: it enables us to manage our development and testing database environments in a quick and simple way without requiring support from a database administrators team.

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For big IT firms like us, data is very important and it only holds its value if it can make sense to us. Therefore, Bigtable's usability is priceless when it comes to decision making based on data.

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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.

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Google provides premium support services for BigTable which is absolutely blazing fast similar to Bigtable's performance.

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As a hosted solution, that can be managed easily from the Google cloud platform, it enables the teams to think about business use cases vs thinking about the management of the database itself. It is easily to scale it up when you need more throughput or storage. This keeps the developers and the product folks happy.

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I found Oracle Autonomous Database very secure to store data and private information.I always feel secure with Oracle Autonomous Databases disaster recovery features.It is very effective to build applications for mobile and desktop devices lesser code using a low code development framework namely Oracle Application Express (ApEx).

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• Building new features that can leverage storage on the edge
• Realtime decision making
• Data enrichment

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• 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.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info