Apache Pig is a programming tool for creating MapReduce programs used in Hadoop.
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Oracle Database
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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.
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Apache Pig
Oracle Database
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Apache Pig
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Apache Pig
Oracle Database
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Apache Pig
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Relational Databases
Comparison of Relational Databases features of Product A and Product B
Apache Pig is best suited for ETL-based data processes. It is good in performance in handling and analyzing a large amount of data. it gives faster results than any other similar tool. It is easy to implement and any user with some initial training or some prior SQL knowledge can work on it. Apache Pig is proud to have a large community base globally.
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.
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.
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.
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.
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
Apache Pig might help to start things faster at first and it was one of the best tool years back but it lacks important features that are needed in the data engineering world right now. Pig also has a steeper learning curve since it uses a proprietary language compared to Spark which can be coded with Python, Java.
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
Higher learning curve than other similar technologies so on-boarding new engineers or change ownership of Apache Pig code tends to be a bit of a headache
Once the language is learned and understood it can be relatively straightforward to write simple Pig scripts so development can go relatively quickly with a skilled team
As distributed technologies grow and improve, overall Apache Pig feels left in the dust and is more legacy code to support than something to actively develop with.