Apache Derby vs. Google Compute Engine

If you need a SQL-capable database-like solution that is file-based and embeddable in your existing Java Virtual Machine processes, Apache Derby is an open-source, zero cost, robust and performant option. You can use it to store structured relational data but in small files that can be deployed right alongside with your solution, such as storing a set of relational master data or configuration settings inside your binary package that is deployed/installed on servers or client machines.

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You can use Google Cloud Compute Engine as an option to configure your Gitlab, GitHub, and Azure DevOps self-hosted runners. This allows full control and management of your runners rather than using the default runners, which you cannot manage. Additionally, they can be used as a workspace, which you can provide to the employees, where they can test their workloads or use them as a local host and then deploy to the actual production-grade instance.

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• Apache Derby is SMALL. Compared to an enterprise scale system such as MSSQL, it's footprint is very tiny, and it works well as a local database.
• The SPEED. I have found that Apache Derby is very fast, given the environment I was developing in.
• Based in JAVA (I know that's an obvious thing to say), but Java allows you to write some elegant Object Oriented structures, thus allowing for fast, Agile test cases against the database.
• Derby is EASY to implement and can be accessed from a console with little difficulty. Making it appropriate for everything from small embedded systems (i.e. just a bash shell and a little bit of supporting libraries) to massive workstations.

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• Scaling - whether it's traffic spikes or just steady growth, Google Compute Engine's auto-scaling makes sure we've got the compute power we need without any manual juggling acts
• Load balancing - Keeping things smooth with that load balancing across multiple VMs, so our users don't have to deal with slow load times or downtime even when things get crazy busy
• Customizability - Mix and match configs for CPU, RAM, storage and whatnot to suit our specific app needs

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• It may not scale as well as some more mature database products.
• Used it primarily from the command line with openjpa and jdbc, and from third-party clients such as Squirrel.
• May benefit by providing more sophisticated tools to optimize query performance.

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• Built-in monitoring via Stackdriver is quite expensive for what it provides.
• Initially provided quotas (ie. max compute units one can use) are very low and it took several requests to get an appropriate amount.
• Support on GCE is limited to their knowledge base and forums. For more hands-on support provided by Google, you must pay for their Premium services.

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Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.

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Having interacted with several cloud services, GCE stands out to me as more usable than most. The naming and locating of features is a little more intuitive than most I've interacted with, and hinting is also quite helpful. Getting staff up to speed has proven to be overall less painful than others.

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Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes

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It works great all the time except for occasional issues, but overall, I am very happy with the performance. It delivers on the promise it makes and as per the SLAs provided. Networking is great with a premium network, and AZs are also widespread across geographies. Overall, it is a great infra item to have, which you can scale as you want.

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• The documentation needs to be better for intermediate users - There are first steps that one can easily follow, but after that, the documentation is often spotty or not in a form where one can follow the steps and accomplish the task. Also, the documentation and the product often go out of sync, where the commands from the documentation do not work with the current version of the product.
• Google support was great and their presence on site was very helpful in dealing with various issues.

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SQLite is another open-source zero-cost file-based SQL-capable database solution and is a good alternative to Apache Derby, especially for non-Java-based solutions. We chose Apache Derby as it is Java-based, and so is the solution we embedded it in. However, SQLite has a similar feature set and is widely used in the industry to serve the same purposes for native solutions such as C or C++-based products.

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Google Compute Engine provides a one stop solution for all the complex features and the UI is better than Amazon's EC2 and Azure Machine Learning for ease of usability. It's always good to have an eco-system of products from Google as it's one of the most used search engine and IoT services provider, which helps with ease of integration and updates in the future.

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It works really well with other Google Cloud services, making it easy to build scalable solutions across different teams and locations.

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• Being Open source, the resources spent on the purchase of the product are ZERO.
• Contrary to popular belief, open source software CAN provide support, provided that the developers/contributors are willing to answer your emails.
• Overall, the ROI was positive: being able to experiment with an open source technology that could perform on par with the corporate products was promising, and gave us much information about how to proceed in the future.

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• With Google Compute we don't have the overhead of managing our own data centers reducing costs and reducing the staff needed to manage systems.
• As I said earlier, Google's costs are ~1/2 of AWS, so we are able to see a ROI much faster.

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