MySQL is a popular open-source relational and embedded database, now owned by Oracle.
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Oracle Database
Score 8.3 out of 10
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Oracle Database, currently in edition 23ai, is a converged, multimodel database management system. It is designed to simplify development for AI, microservices, graph, document, spatial, and relational applications.
$0.05
per hour
TensorFlow
Score 7.7 out of 10
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TensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.
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Oracle Base Database Service - Standard
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Oracle Base Database Service - Enterprise
$0.1075
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Oracle Base Database Service - High Performance
$0.2218
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Community Pulse
MySQL
Oracle Database
TensorFlow
Considered Multiple Products
MySQL
Verified User
Engineer
Chose MySQL
MySQL offers some of the features as Oracle Database 12c, however, there are many crucial ones that are missed. Features such as OLAP, really make Oracle Database 12c a clear winner here. We use both databases in our organization for separate reasons, MySQL for prototyping, and …
Of course compare to no SQL databases it's slower but there is a completely different use case for them... In my opinion it is better than PostgreSQL, it's easier to configure and has the same performance, or approximately the same. Of course Oracle Database is a way bigger …
MySQL was the first option due to the existing knowledge, and after using other databases, it also appeared to be the most predictable in terms of costs
Rest all the big brand databases incure high licensing cost giving almost the same value that MySQL is giving being an open source database. Other databases like Oracle, MS SQL servers need extensive resource along with a huge team to manage those databases. However, thats not …
As I have been commenting in our company, we have solved our performance problems and responses obtaining speed in the queries occupies less disk space, in addition to its price and all the tools of great Scope it possesses.
Having used both PostgreSQL and Microsoft SQL Server, I can tell that MySQL performs admirably in a Linux setting. When compared to Microsoft SQL Server, the extra benefit is the minimal or nonexistent licence fee. We find that MySQL's programming interface is particularly …
Before MySQL, our team was exploring and evaluating different options for a good RDMS (relational database management system) service. We explored Oracle, MSSQL, and Google BigQuery. Most of these are costly and not easy to maintain in the long run in terms of price especially …
MySQL has most of the functionality of other, very costly, alternatives without the big price tag. It is open-source with improvements coming at a relatively good rate. It is not as robust as those other offerings and can have some challenging points at scale for large …
Microsoft SQL can be considered as an enterprise level software since it is recommended for large businesses. Microsoft SQL has some unique categories like big data processing, DBMS, etc. whereas MySQL is not capable of handling such features. I guess this is how these both …
I would choose Oracle 11g, 12c for more complex ventures which require financials and complex logic. I would choose MySQL for simpler applications which simply need to interface data to a backend. I selected MySQL in this case because it is free and much simpler to install—it …
Familiarity: With MySQL, I know what to expect, and that goes a long way. Also, since it adheres fairly close to SQL '92, It's relatively easy to construct queries, views, etc. without a steep learning curve. Also, RAM usage is important (this is true of any RDBMS …
We have used Oracle as our clinical databases that stores patient records. In this project we didn't used Oracle but separately built MySQL based data infrastructure as this is an independent scientific research project. Oracle is great overall, with most of functionalities …
I've used both Oracle and MySQL. I like both database technologies. Both of them provide great solutions. Each one has their own benefits based on the requirement and right environment. The point is to find the right environment to use and compare price/performance/scalability.
MySQL does not provide anywhere near the user interface or features that Oracle Database 12c provides. Building REST endpoints on MySQL is a much more challenging process and integrating it with a web app is much more complicated than building an ORDS endpoint within the Oracle …
We currently use all of the above database technologies in different applications, but where the application is mission-critical we use Oracle. Microsoft SQL Server is good for canned applications such as back-office or HR. MySQL does not have the same level of logging or …
IBM DB2 is extremely heavy as compared to Oracle and is expensive for the price we pay for the product. MySQL doesn’t have most of the features that Oracle has.
Oracle is placed in a good spot against its competitors. It has advantages over its competitors in its legacy stability and high availability. A common engine to handle relational, JSON, Vector, and graph data makes it more cost-effective. Given all the good features, the …
The Oracle database was selected before I started working on the project, so I can't tell the reasons behind the choice. However, it was recognized as the best suited for holding several million records for related entities and was preferred over NoSQL options.
Oracle 12c is good for all business applications but still consider Microsoft SQLServer for internal/other applications to save on cost.
Verified User
Consultant
Chose Oracle Database
Oracle Database is best in business, consistent, and robust. Even the standard version is sufficient for the best performance. The main thing is I have never seen corruption and in my opinion, it is best when used with Linux.
Verified User
Engineer
Chose Oracle Database
Microsoft SQL is just as stable and almost as sellable with a much lower cost of ownership (staff and licensing). But as our primary application doesn't support Microsoft SQL we had to license Oracle.
Exadata is expensive and we decided to switch to 12c for the sake of consolidating and keep up with Oracles initiative to move towards cloud. Maybe in the future.
Oracle is more of an enterprise-level database than Access and SAP Adaptive Server Enterprise isn't getting developed much (some people wonder how close it is to end of life) but SQL Server is miles ahead of Oracle IMO in terms of user experience and comparable in terms of …
Oracle 12c is able to support daily operations that might be required. Of course, Exadata is a powerful machine that is definitely fit for big scale but requires high demand of both CPU, IO, and memory processing. Also the one engineered system saves lots of time to build the …
It's the Oracle Support that beats everything else, and a solid contract. Also, all the other features that support Oracle are way ahead of other products.
Oracle completed solution and support is of cause better than open source solutions, we also choose other NoSQL database and Graph database, to address some very particular business use cases
It's easy to scale an Oracle database compared to any others, it's easy to manage many Oracle databases together with lots of administrative and security features.
1. The commercial application required an Oracle database running at the back end 2. Existing Oracle expertise makes it easy to manage an Oracle database 3. Confidence in Oracle databases: No need to worry about performance, scalability.
For some implementations in my company, Oracle Database was selected because all the support, experience, features, continuing development, etc that the product and Oracle's company has been providing so far, but also, it was selected by the system's company that my …
MySQL is best suited for applications on platform like high-traffic content-driven websites, small-scale web apps, data warehouses which regards light analytical workloads. However its less suited for areas like enterprise data warehouse, OLAP cubes, large-scale reporting, applications requiring flexible or semi-structured data like event logging systems, product configurations, dynamic forms.
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.
TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
Learning curve: is big. Newbies will face problems in understanding the platform initially. However, with plenty of online resources, one can easily find solutions to problems and learn on the go.
Backup and restore: MySQL is not very seamless. Although the data is never ruptured or missed, the process involved is not very much user-friendly. Maybe, a new command-line interface for only the backup-restore functionality shall be set up again to make this very important step much easier to perform and maintain.
Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.
For teaching Databases and SQL, I would definitely continue to use MySQL. It provides a good, solid foundation to learn about databases. Also to learn about the SQL language and how it works with the creation, insertion, deletion, updating, and manipulation of data, tables, and databases. This SQL language is a foundation and can be used to learn many other database related concepts.
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.
I give MySQL a 9/10 overall because I really like it but I feel like there are a lot of tech people who would hate it if I gave it a 10/10. I've never had any problems with it or reached any of its limitations but I know a few people who have so I can't give it a 10/10 based on those complaints.
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.
We have never contacted MySQL enterprise support team for any issues related to MySQL. This is because we have been using primarily the MySQL Server community edition and have been using the MySQL support forums for any questions and practical guidance that we needed before and during the technical implementations. Overall, the support community has been very helpful and allowed us to make the most out of the community edition.
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.
Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
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
MongoDB has a dynamic schema for how data is stored in 'documents' whereas MySQL is more structured with tables, columns, and rows. MongoDB was built for high availability whereas MySQL can be a challenge when it comes to replication of the data and making everything redundant in the event of a DR or outage.
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
Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
