Google Cloud Dataflow vs. Oracle Database

It is best in cases where you have batch as well as streaming data. Also in some cases where you have batch data right now and in future you will get streaming data. In those cases Dataflow is very good. Also in cases where most of your infra is on GCP. It might not be good when you already are on AWS or Azure. And also you want in-depth control over security and management. Then you can directly use Apache beam over Dataflow.

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We migrated from NoSQL to an Oracle database. One of the reasons was robust backup and recovery options available in the Oracle database, which provide zero data loss. A transactional database like Oracle is a better fit for our use case than NoSQL. On a large scale, deployment was evaluated as a cheaper option than the NoSQL engine. This conclusion came even after considering Oracle license is expensive.

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• Streaming, Real time work load
• Batch processing
• Auto scaling
• flexible pricing

• Supports most of the Operating Systems like Unix, Linux and Windows Server.
• It works well in high load environment under intense parallel transactions setup.
• Highly reliable DBMS, especially RAC is very much reliable.
• Well managed and predictable release of security patches.
• We have highly scaled it from on-prem to a cloud cluster environment for our product.
• One of the best-performing DBMSs on Linux machines under test delivers high throughput (QPS).

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• More templates for Bigquery and App Engine. There is only limited options for templates so the things we use can limit.
• I would like native connectors for Excel (XLSX) to reduce the need for custom wrappers in financial pipelines.
• Debugging Google Cloud Dataflow using only logs in Cloud Logging can be overwhelming sometimes, and it’s not always obvious which specific element in the flow caused a failure. IT uses a lot of time.

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• The memory demand and management makes it impossible to run it in a container.
• It is hard to perform local unit testing with Oracle even using the personal edition (aggressive all the available memory grab for itself).
• Lack of built in database migrations (e.g. as Flyway).
• The need to install the Oracle client in addition to its drivers.
• The cost of running it, especially in the Cloud.
• Comes with very spartan community grade client/management tools whereas the commercial offerings tend to demand a premium price.

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There is a lot of sunk cost in a product like Oracle 12c. It is doing a great job, it would not provide us much benefit to switch to another product even if it did the same thing due to the work involved in making such a switch. It would not be cost effective.

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It really saved a lot of time and it's flexibility really can give you infra which is future-proof for most of the use cases may it be streaming or batch data. And with this you can avoid use of resource-heavy big data offerings.

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Many of the powerful options can be auto-configured but there are still many things to take into account at the moment of installing and configuring an Oracle Database, compared with SQL Server or other databases. At the same time, that extra complexity allows for detailed configuration and guarantees performance, scalability, availability and security.

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1. I have very good experience with Oracle Database support team. Oracle support team has pool of talented Oracle Analyst resources in different regions. To name a few regions - EMEA, Asia, USA(EST, MST, PST), Australia. Their support staffs are very supportive, well trained, and customer focused. Whenever I open Oracle Sev1 SR(service request), I always get prompt update on my case timely. 2. Oracle has zoom call and chat session option linked to Oracle SR. Whenever you are in Oracle portal - you can chat with the Oracle Analyst who is working on your case. You can request for Oracle zoom call thru which you can share the your problem server screen in no time. This is very nice as it saves lot of time and energy in case you have to follow up with oracle support for your case. 3.Oracle has excellent knowledge base in which all the customer databases critical problems and their solutions are well documented. It is very easy to follow without consulting to support team at first.

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Overall the implementation went very well and after that everything came out as expected - in terms of performance and scalability. People should always install and upgrade a stable version for production with the latest patch set updates, test properly as much as possible, and should have a backup plan if anything unexpected happens

Google Cloud Dataproc Cloud Datafusion

Because of a rich user base and support for any critical issue, this is one of the best options to choose. In case the project has a TCO issue, it can compromise and choose Postgres as the best alternative. SQL server is also good and easy to code and maintain but performance is not as good as the Oracle

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• cost saving from managing our own data center for ETL servers
• consumption based pricing
• with auto scaling feature, we were able to expand components to support work load

• Multiple applications can use the same database and still get high performance
• Licensing cost is still a concern compared to the other options available in the market that are very very inexpensive
• Almost a maintenance free database
• Oracle Grid makes life easy in terms of monitoring and managing the databases

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Independently Invited by TrustRadius

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