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diff --git a/MANIFESTO b/MANIFESTO new file mode 100644 index 0000000..3727894 --- /dev/null +++ b/MANIFESTO @@ -0,0 +1,106 @@ +[Note: this is the Redis manifesto, for general information about + installing and running Redis read the README file instead.] + +Redis Manifesto +=============== + +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 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 - We believe in code efficiency. Computers get faster and faster, yet we + believe that abusing computing capabilities is not wise: the amount of + operations you can do for a given amount of energy remains anyway a + significant parameter: it allows to do more with less computers and, at + the same time, having a smaller environmental impact. Similarly Redis is + able to "scale down" to smaller devices. It is perfectly usable in a + Raspberry Pi and other small ARM based computers. Faster code having + just the layers of abstractions that are really needed will also result, + often, in more predictable performances. We think likewise about memory + usage, one of the fundamental goals of the Redis project is to + incrementally build more and more memory efficient data structures, so that + problems that were not approachable in RAM in the past will be perfectly + fine to handle in the future. + +5 - 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. + +6 - 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. Complexity is also a form of lock-in: code that is + very hard to understand cannot be modified by users in an independent way + regardless of the license. One of the main Redis goals is to remain + understandable, enough for a single programmer to have a clear idea of how + it works in detail just reading the source code for a couple of weeks. + +7 - Threading is not a silver bullet. Instead of making Redis threaded we + believe on the idea of an efficient (mostly) single threaded Redis core. + Multiple of such cores, that may run in the same computer or may run + in multiple computers, are abstracted away as a single big system by + higher order protocols and features: Redis Cluster and the upcoming + Redis Proxy are our main goals. A shared nothing approach is not just + much simpler (see the previous point in this document), is also optimal + in NUMA systems. In the specific case of Redis it allows for each instance + to have a more limited amount of data, making the Redis persist-by-fork + approach more sounding. In the future we may explore parallelism only for + I/O, which is the low hanging fruit: minimal complexity could provide an + improved single process experience. + +8 - 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 but + there's no way to make the more complex multi-keys API distributed in an + opaque way without violating our other principles. We don't want to provide + the illusion 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 + trade-offs to the user. + +9 - 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. + +10 - All the above points are put together in what we call opportunistic + programming: trying to get the most for the user with minimal increases + in complexity (hanging fruits). Solve 95% of the problem with 5% of the + code when it is acceptable. Avoid a fixed schedule but follow the flow of + user requests, inspiration, Redis internal readiness for certain features + (sometimes many past changes reach a critical point making a previously + complex feature very easy to obtain). |