Redis Manifesto Back
- Origin: http://oldblog.antirez.com/post/redis-manifesto.htm
- Time: Mar 1st, 2011
Many times I don't know what to exactly reply to feature requests, or questions about why things in Redis are done in a specific way. Most of the time the questions make a lot of sense, there is not just a way to make things in programming, a lot is about your taste, feeling, and ideas about how software should be written. So I tried to condense(濃縮) my feelings about Redis and software development in general in this short manifest, that I'll include in the Redis distribution. There are an infinite number of ways of doing things, this is just the one I and a good part of the Redis community like.
- 1 - A DSL for Abstract Data Types. Redis is a DSL (Domain Specific Language) that manipulates abstract data types and implemented as a TCP daemon. Commands manipulate a key space where keys are binary-safe strings and values are different kinds of abstract data types. Every data type represents an abstract version of a fundamental data structure. For instance Redis Lists are an abstract representation of linked lists. In Redis, the essence of a data type isn't just the kind of operations that the data types support, but also the space and time complexity of the data type and the operations performed upon it.
- 2 - Memory storage is #1. The Redis data set, composed of defined key-value pairs, is primarily stored in the computer's memory. The amount of memory in all kinds of computers, including entry-level servers, is increasing significantly each year. Memory is fast, and allows Redis to have very predictable performance. Datasets composed of 10k or 40 millions keys will perform similarly. Complex data types like Redis Sorted Sets are easy to implement and manipulate in memory with good performance, making Redis very simple. Redis will continue to explore alternative options (where data can be optionally stored on disk, say) but the main goal of the project remains the development of an in-memory database.
- 3 - Fundamental data structures for a fundamental API. The Redis API is a direct consequence of fundamental data structures. APIs can often be arbitrary(隨意的) but not an API that resembles the nature of fundamental data structures. If we ever meet intelligent life forms from another part of the universe, they'll likely know, understand and recognize the same basic data structures we have in our computer science books. Redis will avoid intermediate layers in API, so that the complexity is obvious and more complex operations can be performed as the sum of the basic operations.
- 4 - Code is like a poem; it's not just something we write to reach some practical result. Sometimes people that are far from the Redis philosophy suggest using other code written by other authors (frequently in other languages) in order to implement something Redis currently lacks. But to us this is like if Shakespeare decided to end Enrico IV using the Paradiso from the Divina Commedia. Is using any external code a bad idea? Not at all. Like in "One Thousand and One Nights" smaller self contained stories are embedded in a bigger story, we'll be happy to use beautiful self contained libraries when needed. At the same time, when writing the Redis story we're trying to write smaller stories that will fit in to other code.
- 5 - We're against complexity. We believe designing systems is a fight against complexity. We'll accept to fight the complexity when it's worthwhile but we'll try hard to recognize when a small feature is not worth 1000s of lines of code. Most of the time the best way to fight complexity is by not creating it at all.
- 6 - Two levels of API. The Redis API has two levels: 1) a subset of the API fits naturally into a distributed version of Redis and 2) a more complex API that supports multi-key operations. Both are useful if used judiciously(得當地) but there's no way to make the more complex multi-keys API distributed in an opaque(模糊的) way without violating(侵犯) our other principles. We don't want to provide the illusion(錯覺) of something that will work magically when actually it can't in all cases. Instead we'll provide commands to quickly migrate keys from one instance to another to perform multi-key operations and expose the tradeoffs to the user.
- 7 - We optimize for joy. We believe writing code is a lot of hard work, and the only way it can be worth is by enjoying it. When there is no longer joy in writing code, the best thing to do is stop. To prevent this, we'll avoid taking paths that will make Redis less of a joy to develop.
Thanks to Peter Cooper for reading the draft and helping to make it better.