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+[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).