Differences Between Cassandra vs Redis
Cassandra and Redis both are normally using for fetching and storing huge data very fast and helping to complete live streaming with huge data easily.
As Cassandra is an Apache product, so one of the great benefits of using Cassandra is it support HiveQL (SQL like syntax). Cassandra following structure of normal column/table format oriented database which very much well supported by the historical RDMS. It also not supports full CAP (Consistency, Availability, and Partition Tolerance), can consider the same as AP (availability and partition tolerance). Suppose you have a business requirement to write or store more data into the system rather read data, then Cassandra will be one of the good options. That’s why Cassandra is too popular with some specific industries like banking or financial where the normal attitude to writing more than reading (considering entire data including transaction data).
Redis is faster than Cassandra in form of big data fetching and storing especially in the case of live streaming. Redis normally maintained a disk backed in-memory database. It normally maintained master-slave architecture (as the following a line with Hadoop Architecture). And the very interesting point, it mainly followed CP (means consistency and Partition Tolerance) in CAP (Consistency, Availability, and Partition Tolerance) theorem. If an organization really have rapid changing huge data then it will be great to use Redis without thinking any other option. But as Radis mainly in memory database it should have some approximate data size estimation, which considering memory size and all. For any kind of analytics with real data and integrate real-time data streaming with huge data, Redis always be a great option to any industry.
Now it is one of the big concern for any software architect to choose an exact tool for processing huge live date based on industry requirement. Sometimes for one specific organization have two different kinds of requirements where may need to follow both Cassandra vs Redis.
Head to Head Comparison Between Cassandra and Redis (Infographics)
Below is the top 6 comparison between Cassandra and Redis:
Key Differences Between Cassandra and Redis
Below are the lists of points, describe the key differences between Cassandra and Redis:
- Cassandra has been preferable to write more and read less situation. Whereas Redis always used for rapidly changed data on both write and read.
- Cassandra can hold huge data in a tabular format which support HiveQL (SQL like language), whereas Redis store the data as a key-value pair which normally not supported any SQL like language.
- Cassandra entirely has written in Java language, whereas Redis written in C, C++.
- Cassandra normally followed disk-bound in-memory database, whereas Redis following disk backed in-memory database.
- Compare to CAP (Consistency, Availability, and Partition Tolerance) theorem, Cassandra following AP (Availability and Partition Tolerance) whereas Redis following CP (Consistency and Partition Tolerance).
- Disk swap can be possible for Cassandra, so have importance on VM or Disk store, whereas VM and Disk Store are abandoned for Redis as currently, disk swap is not available for Redis.
- Cassandra is a tuneable trade-off policy in case of distribution and replication (N, R, W). Whereas Redis following proper Master-Slave replication in-memory database.
- As Cassandra supported normal query type language, so query by column or range of verities keys or any data searching criteria can be easily reachable. Whereas Redis always returning simple value or hash tables by key as it stored data as key-value pair always.
- Cassandra following big table like features, it holding column or column families for the list of data. Whereas Redis doesn’t have column concept, it stored data as key-value pair always.
- For executing any range queries Redis will be always better as it has sorted set option with high score table structure, whereas for Cassandra need to write a proper query to fetch those data which is costly and not much fast like Redis.
- Redis has some special utility like has set, has lists, has hashes which help for doing union, difference, inter-sector, returning queue or blocking POP, returning an object of multiple fields. Whereas for Cassandra we always need to write queries to do the same.
Cassandra and Redis Comparison Table
Below is the comparison table between Cassandra and Redis.
| BASIS FOR
COMPARISON |
Cassandra | Redis |
| Written In | Java Programing Language | C, C++ Programming Language |
| Main Utility | Store huge datasets easily almost like SQL. | Storing and reading huge data are very fast. |
| License | Apache proving license. | BSD providing license. |
| Protocol | Thrift, binary CQL3 | Telnet like and always binary safe. |
| Best Used | If the requirement to write data more than reading, then Cassandra is always a wonderful option any time. And if all the component of provided system set up in Java then again Apache stuff like Cassandra will be an automatic choice. | If a requirement of changing huge data very frequently and rapidly then Redis is the correct option to choose always. But database size for Redis always be foreseeable, size should be maintained as per memory size. |
| Example | Industry where mainly requirement to write faster than read always, as for example Banking, Financial Industry. | For any real-time activity like stock price analysis. |
Conclusion
Considering above discussion our final conclusion of choosing Cassandra or Redis will depend on kind of below parameters:
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Do you need Key-Value relationship for your current implementation? – Then Redis is always best.
Is there rapidly changed on data? – Again Redis is the best choice.
If Write would be more than reading? – Cassandra will be the best choice.
If Read is more than write or work with very frequent data? – Then Redis will be a good choice.
Considering Fault tolerance option – then Cassandra will little better than Redis as it followed proper Hadoop architecture.
In case of persistence session data – Redis will be better.
A final conclusion is, if an organization needs to store huge data and used the same for analyzing report in some schedule time gap, then Cassandra will be a very good option for any condition.
But if the organization wants to generate analytics on current live streaming data every time then obviously Redis is always the best option. Because Redis is faster than Cassandra anyway in case of reading and writing huge data especially live streaming data.
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