Google Cloud Dataflow vs. SAP Replication Server

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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I asked questions about a warm standby and multicast replication. We ended up using bi-directional replication and a warm standby db. Having 3 or more live OLTP DB's where each was read-write was going to be difficult to manage for contention if the same table was being updated. We stuck with an easier solution to have only two OLTP's, and then used additional DB's as read-only DW's.

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

• guaranteed delivery
• high availability
• scalable
• low latency
• data transformation

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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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• Data Reconciliation Functionality.

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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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SAP support has been outstanding. They have quick response times and always meet their SLAs. Any time we have an issue that needs to be researched they are able to get back to us quickly with resolution.

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Google Cloud Dataproc Cloud Datafusion

Hands down Sybase has the best replication

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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

• A positive is that it allow quick business decision making on the basis of real time data. Huge time saving for business.

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