/*! @page architecture WiredTiger Architecture

The WiredTiger data engine is a high performance, scalable, transactional,
production quality, open source, NoSQL data engine, created to maximize the
value of each computer you buy:

- WiredTiger offers both low latency and high throughput (in-cache reads
require no latching, writes typically require a single latch),

- WiredTiger handles data sets much larger than RAM without performance
or resource degradation,

- WiredTiger has predictable behavior under heavy access and large
volumes of data,

- WiredTiger offers transactional semantics without blocking,

- WiredTiger stores are not corrupted by torn writes, reverting to the
last checkpoint after system failure,

- WiredTiger supports petabyte tables, records up to 4GB, and record
numbers up to 64-bits.

WiredTiger's design is focused on a few core principles:

@section multi_core Multi-core scaling

WiredTiger scales on modern, multi-CPU architectures.  Using a variety of
programming techniques such as hazard pointers, lock-free algorithms, fast
latching and message passing, WiredTiger performs more work per CPU core than
alternative engines.

WiredTiger's transactions use optimistic concurrency control algorithms that
avoid the bottleneck of a centralized lock manager.  Transactional operations
in one thread do not block operations in other threads, but strong isolation is
provided and update conflicts are detected to preserve data consistency.

@section cache Hot caches

WiredTiger supports both row-oriented storage (where all columns of a
row are stored together), and column-oriented storage (where groups of
columns are stored in separate files), resulting in more efficient
memory use.  When reading and writing column-stores, only the columns
required for any particular query are maintained in memory.
Column-store keys are derived from the value's location in the table
rather than being physically stored in the table, further minimizing
memory requirements.  Finally, row-and column-stores can be
mixed-and-matched at the table level: for example, a row-store index can
be created on a column-store table.

WiredTiger supports @ref lsm, where updates are buffered in small files
that fit in cache for fast random updates, then automatically merged into
larger files in the background so that read latency approaches that of
traditional Btree files.  LSM trees automatically create Bloom filters to
avoid unnecessary reads from files that cannot containing matching keys.

WiredTiger supports different-sized Btree internal and leaf pages in the
same file.  Applications can maximize the amount of data transferred in
each I/O by configuring large leaf pages, and still minimize CPU cache
misses when searching the tree.

WiredTiger supports key prefix compression and value dictionaries,
reducing the amount of memory keys and values require.

WiredTiger supports static encoding with a configurable Huffman engine,
which typically reduces the amount of information maintained in memory
by 20-50%.

@section io Making I/O more valuable

WiredTiger uses compact file formats to minimize on-disk overhead.
WiredTiger does not store page content indexing information on disk,
instead, WiredTiger instantiates content indexing information either
when pages are read from disk or on demand.  This simplifies the on-disk
file format and in the case of small key/value pairs, typically reduces
the amount of information written to disk by 20-50%.

WiredTiger supports variable-length pages, meaning there is less wasted
space for large objects, and no need for compaction as pages grow and
shrink naturally when key/value pairs are inserted or deleted.

WiredTiger supports block compression on table pages.  Because
WiredTiger supports variable-length pages, pages do not have to shrink
by a fixed amount in order to benefit from block compression.  Block
compression is selectable on a per-table basis, allowing applications
to choose the compression algorithm most appropriate for their data.
Block compression typically reduces the amount of information written
to disk by 30-80%.

WiredTiger supports leaf pages of up to 512MB in size.  Disk seeks are
less likely when reading large amounts of data from disk, significantly
improving table scan performance.

Also, as noted in the @ref cache section, WiredTiger supports
column-store formats, prefix compression and static encoding.  While
each of these features makes WiredTiger's use of memory more efficient,
they also maximize the amount of useful data transferred per disk I/O.

@section quality Production quality

WiredTiger is production quality, supported software, engineered for the
most demanding application environments.  For example, as a no-overwrite
data engine, torn writes can never corrupt a WiredTiger data store.

WiredTiger includes verification support so you can verify data sets,
and salvage support as a last-ditch protection: data can be retrieved
even if it somehow becomes corrupted.

@section nosql NoSQL and Open Source

WiredTiger is an Open Source, NoSQL data engine.  See the @ref license
for details.

*/
