MySQL vs. ParAccel

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.

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Actian matrix is not good for small data sets. If you have a limited data pool, or do not plan on having multiple users/clients accessing a data source, stick with a more traditional relational database model - Access for the truly small user base, or a DB2 or Oracle back end if your going to have multiple users, and moderate sized data. Actian is for LARGE data sets (Big Data, in the industry parlance). Millions of rows of data from multiple sources with various down stream systems accessing the database. It is for data analytics of large data groups and intense data mining.

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• Stable - it just runs, with minimal downtime or errors
• Fast - well-structured data is quickly written and read
• Secure - MySQL is easy to keep data secure from people and applications that shouldn't see it
• Easy to use - SQL is industry standard so no problems with adding, editing and reading data stored in MySQL

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• Super fast. Aggregate query such as SUM(), Count() returns result within seconds from a table with more than billion records.
• Excellent data compression.
• Easy maintenance. We managed this database without having a full time DBA.
• Support ANSI SQL and ODBC/JDBC. It's easy to connect to this database from other systems.

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• 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.

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• Some of the bugs were annoying and QA definitely needs improvement
• Connectivity to Informatica and ETL providers
• Workload management could be better like when you compare with Teradata

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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.

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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.

I wish to give higher rating for the speed and efficiency in handling the queries, but only 6 because of consistent bugs we encounter

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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.

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• Faster initial response
• Trained professionals
• Very helpful in resolving issues

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1. Estimate your data size. 2. Test, test, and test.

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Leader failover setup is the toughest and lack of proper documentation is making things tough.

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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.

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Actian Matrix is our first big data analytics storage platform, and as I was not involved in the POC process to compare it to other products out on the market, unfortunately I cannot say if it is better than other Big Data storage options. I can say that it out performs products such as Oracle or UDB in regards to the volume of data it can easily index and handle.

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• As it is an open source solution through community solution, we can use it in a multitude of projects without cost license
• The acquisition by Oracle makes you need to contract support for the enterprise version
• If you have knowledge about oracle databases, you can get more out of the enterprise version

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• ROI is great, less spending on full time DBA and that money could be use to add additional node.
• Negative - Not many developers are well aware of this tool, it takes some time to learn.

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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