MySQL is a popular open-source relational and embedded database, now owned by Oracle.
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Redis is an open source in-memory data structure server and NoSQL database.
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Apache Cassandra
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Chose Apache Cassandra
Cassandra is the only NoSQL database I have extensive experience with. In terms of other open source database solutions, I can say that I like Cassandra as much or equally as traditional Oracle MySQL, and a lot more than PostgresSQL. The decision to use Cassandra was driven by …
Against HBase, writes were faster. Reads not so much. Also ability to store in other formats would be good (such as objects). Compared to aerospike, does not compare. Aerospike blows it out of water.
Technology selection should be done based on the need and not based on buzz words in the market (google searching). If your data need flat file approach and more searchable based on index and partition keys, then it's better to go for Cassandra. Cassandra is a better choice …
We also evaluated mySQL and mongoDB. Both of them have their strengths and weaknesses but they are less suited for storing massive amounts of time series data. In addition, they are not elastic by nature and we required a "future-proof" solution as it was difficult to estimate …
Is not a drop-in replacement for any of the things listed above. MySQL has it's purpose and use-cases, same as those. It's a low-cost solution for high read/low write applications and works very well when used in the right circumstances. Support can be purchased from various …
SQLite - Is the goto DB for Mobile/Desktop Apps. Its not as elaborate as Mysql but since its a RDBMS it provides all the basic features and its lite. We use mysql at the backend and for desktop app we use SQLite
postgres - Its a formidable opponent. It is fast and reliable 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 …
Comparing MongoDB vs MySQL performance is difficult, since both management systems are extremely useful and the core differences underly their basic operations and initial approach. However, MongoDB vs MySQL is a hot argument that has been going on for a while now: mature …
MySQL holds its own in terms of SQL engine speed and storage capability, but database administration is where MySQL really shines. Other products that I've used offer little in terms of tuning or portability. Managing a MySQL database is relatively painless out of the box and …
If you are looking for a relational database (depending on your app), MySQL is a good place to start. MongoDB and Cassandra are NoSQL options (very powerful). I am more inclined towards PostgreSQL as it's more scalable over time. MySQL was bought by Oracle and the community …
We are big users of MySQL and PostgreSQL. We were looking at replacing our aging web page caching technology and found that we could do it in SQL, but there was a NoSQL movement happening at the time. We dabbled a bit in the NoSQL scene just to get an idea of what it was about …
UI isn't that great compared to the other competitors. The management of our memcached cluster was becoming pretty complicated as the application grew in size. Redis is a much better option compared to memcached. Redis is bit unreliable compared to the alternative RabbitMQ …
Every time you don't need a document DB, you can't go wrong with Redis over MongoDB. Google Cloud Pub/Sub may have solved one use case, but we'd still have to deploy Redis instances for other use cases, and adding another tech stack would only add complexity to our …
Redis was initially in the list of competitors like Aerospike, Cassandra, MongoDB.The major point that outset all others is that it provides a number of read and writes to the database that no one can match. Another major factor is Redis really knows the basic components that …
As we perform a lot of deployments to AWS, we have the option of easily using a cache layer with either Memcache or Redis. We almost always choose Redis as it can solve more problems in production than Memcache in our experience. There is some overlap between what Redis can do …
We chose Redis over Memcached and Couchbase for its performance, cost, support, and ease of use. Couchbase probably would have worked as well, but it seemed a bit overkill for our use cases.
Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.
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.
Redis has been a great investment for our organization as we needed a solution for high speed data caching. The ramp up and integration was quite easy. Redis handles automatic failover internally, so no crashes provides high availability. On the fly scaling scale to more/less cores and memory as and when needed.
Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.
Easy for developers to understand. Unlike Riak, which I've used in the past, it's fast without having to worry about eventual consistency.
Reliable. With a proper multi-node configuration, it can handle failover instantly.
Configurable. We primarily still use Memcache for caching but one of the teams uses Redis for both long-term storage and temporary expiry keys without taking on another external dependency.
Fast. We process tens of thousands of RPS and it doesn't skip a beat.
Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.
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.
We had some difficulty scaling Redis without it becoming prohibitively expensive.
Redis has very simple search capabilities, which means its not suitable for all use cases.
Redis doesn't have good native support for storing data in object form and many libraries built over it return data as a string, meaning you need build your own serialization layer over it.
I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.
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.
We will definitely continue using Redis because: 1. It is free and open source. 2. We already use it in so many applications, it will be hard for us to let go. 3. There isn't another competitive product that we know of that gives a better performance. 4. We never had any major issues with Redis, so no point turning our backs.
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.
It is quite simple to set up for the purpose of managing user sessions in the backend. It can be easily integrated with other products or technologies, such as Spring in Java. If you need to actually display the data stored in Redis in your application this is a bit difficult to understand initially but is possible.
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.
The support team has always been excellent in handling our mostly questions, rarely problems. They are responsive, find the solution and get us moving forward again. I have never had to escalate a case with them. They have always solved our problems in a very timely manner. I highly commend the support team.
We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra
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.
We are big users of MySQL and PostgreSQL. We were looking at replacing our aging web page caching technology and found that we could do it in SQL, but there was a NoSQL movement happening at the time. We dabbled a bit in the NoSQL scene just to get an idea of what it was about and whether it was for us. We tried a bunch, but I can only seem to remember Mongo and Couch. Mongo had big issues early on that drove us to Redis and we couldn't quite figure out how to deploy couch.
I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.
Redis has helped us increase our throughput and server data to a growing amount of traffic while keeping our app fast. We couldn't have grown without the ability to easily cache data that Redis provides.
Redis has helped us decrease the load on our database. By being able to scale up and cache important data, we reduce the load on our database reducing costs and infra issues.
Running a Redis node on something like AWS can be costly, but it is often a requirement for scaling a company. If you need data quickly and your business is already a positive ROI, Redis is worth the investment.
