[Note: this is the Redis manifesto, for general information about
installing and running Redis read the README file instead.]
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 - 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 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 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.