Skip to content
This repository has been archived by the owner on Jan 27, 2021. It is now read-only.

Commit

Permalink
Merge pull request #8 from zopefoundation/new-overview
Browse files Browse the repository at this point in the history
new overview
  • Loading branch information
jimfulton committed Sep 30, 2015
2 parents 7b76d07 + 86548ca commit ccf6a3a
Showing 1 changed file with 182 additions and 25 deletions.
207 changes: 182 additions & 25 deletions index.rst
Expand Up @@ -2,38 +2,195 @@
ZODB - a native object database for Python
==========================================

Don't squeeze your objects into tables: store them in an object database.
Because ZODB is an object database:

Overview
========
- no separate language for database operations

Python programs are written with the object-oriented paradigm. You use objects
that reference each other freely and can be of any form and shape: no object
has to adhere to a specific schema and can hold arbitrary information.
- very little impact on your code to make objects persistent

Storing those objects in relational databases requires you to give up on the
freedom of reference and schema. The constraints of the relational model
reduces your ability to write object-oriented code.
- no database mapper that partially hides the database.

The ZODB is a native object database, that stores your objects while allowing
you to work with any paradigms that can be expressed in Python. Thereby your
code becomes simpler, more robust and easier to understand.
Using an object-relational mapping **is not** like using an object database.

Also, there is no gap between the database and your program: no glue code to
write, no mappings to configure. Have a look at the tutorial to see how easy
it is.
- almost no seam between code and database.

Some of the features that ZODB brings to you:
Check out the :doc:`documentation/tutorial`!

* Transparent persistence for Python objects
* Full ACID-compatible transaction support (including savepoints)
* History/undo ability
* Efficient support for binary large objects (BLOBs)
* Pluggable storages
* Scalable architecture
Transactions
============

Make programs easier to reason about.

Documentation
Transactions are atomic
Changes made in a transaction are either saved in their entirety or
not at all.

This makes error handling a lot easier. If you have an error, you
just abort the current transaction. You don't have to worry about
undoing previous database changes.

Transactions provide isolation
Transactions allow multiple logical threads (threads or processes)
to access databases and the database prevents the threads from
making conflicting changes.

This allows you to scale your application across multiple threads,
processes or machines without having to use low-level locking
primitives.

You still have to deal with concurrency on some level. For
timestamp-based systems like ZODB, you may have to retry conflicting
transactions. With locking-based systems, you have to deal with
possible deadlocks.

Transactions effect multiple objects
Most NoSQL databases don't have transactions. Their notions of
consistency are much weaker, typically applying to single documents.
There can be good reasons to use NoSQL databases for their extreme
scalability, but otherwise, think hard about giving up the benefits
of transactions.

ZODB transaction support:

- `ACID <https://en.wikipedia.org/wiki/ACID>`_ transactions with
`snapshot isolation
<https://en.wikipedia.org/wiki/Snapshot_isolation>`_

- Distributed transaction support using two-phase commit

This allows transactions to span multiple ZODB databases and to span
ZODB and non-ZODB databases.

Other notable ZODB features
===========================

Pluggable layered storage
ZODB has a pluggable storage architecture. This allows a variety of
storage schemes including memory-based, file-based and distributed
(client-server) storage. Through storage layering, storage
components provide compression, encryption, replication and more.

Database caching with invalidation
Every database connection has a cache that is a consistent partial database
replica. When accessing database objects, data already in the cache
is accessed without any database interactions. When data are
modified, invalidations are sent to clients causing cached objects
to be invalidated. The next time invalidated objects are accessed
they'll be loaded from the database.

This makes caching extremely efficient, but provides some limit to
the number of clients. The server has to send an invalidation
message to each client for each write.

Easy testing
ZODB provides in-memory storage implementations as well as
copy-on-write layered "demo storage" implementations that make testing
database-related code very easy.

Time travel
ZODB storages typically add new records on write and remove old
records on "pack" operations. This allows limited time travel, back
to the last pack time. This can be very useful for forensic
analysis.

Binary large objects, Blobs
Many databases have these, but so does ZODB.

In applications, Blobs are files, so they can be treated as files in
many ways. This can be especially useful when serving media. If you
use AWS, there's a Blob implementation that stores blobs in S3 and
caches them on disk.

When should you use ZODB?
=========================

You want to focus on your application without writing a lot of database code.
Even if find you need to incorporate or switch to another database
later, you can use ZODB in the early part of your project to make
initial discovery and learning much quicker.

Your application has complex relationships and data structures.
In relational databases you have to join tables to model complex
data structures and these joins can be tedious and expensive. You
can mitigate this to some extent in databases like Postgres by using
more powerful data types like arrays and JSON columns, but when
relationships extend across rows, you still have to do joins.

In NoSQL databases, you can model complex data structures with
documents, but if you have relationships across documents, then you
have to do joins and join capabilities in NoSQL databases are
typically far less powerful and transactional semantics typically don't
cross documents, if they exist at all.

In ZODB, you can make objects as complex as you want and cross
object relationships are handled with Python object references.

You access data through object attributes and methods.
If your primary object access is search, then other database
technologies might be a better fit.

ZODB has no query language other than Python. It's primary support
for search is through mapping objects called BTrees. People have
build higher-level search APIs on top of ZODB. These work well
enough to support some search.

You read data a lot more than you write it.
ZODB caches aggressively, and if you're working set fits (or mostly
fits) in memory, performance is very good because it rarely has to
touch the database server.

If your application is very write heavy (e.g. logging), then you're
better off using something else. Sometimes, you can use a database
suitable for heavy writes in combination with ZODB.

Need to test logic that uses your database.
ZODB has a number of storage implementations, including layered
in-memory implementations that make testing very easy.

A database without an in-memory storage option can make testing very
complicated.

When should you *not* use ZODB?
===============================

- Search is a dominant data access path

- You have high write volume

- Caching is unlikely to benefit you

This can be the case when write volume is high, or when you tend to
access small amounts of data from a working set way too large to fit in
memory and when there's no good mechanism for dividing the working
set across application servers.

- You need to use non-Python tools to access your database.

especially tools designed to work with relational databases

How does ZODB scale?
====================

Not as well as many technologies, but some fairly large applications
have been built on ZODB.

At Zope Corporation, several hundred newspaper content-management
systems and web sites were hosted using a multi-database configuration
with most data in a main database and a catalog database. The
databases had several hundred gigabytes of ordinary database records
plus multiple terabytes of blob data.

ZODB is mature
==============

ZODB is very mature. Development started in 1996 and it has been used
in production in thousands of applications for many years.

ZODB is in heavy use in the `Pyramid <http://www.pylonsproject.org/>`_
and `Plone <https://plone.org/>`_ communities and in many other
applications.

Learning more
=============

.. toctree::
Expand Down Expand Up @@ -61,7 +218,7 @@ Community and contributing
Discussion occurs on the `ZODB mailing list
<https://groups.google.com/forum/#!forum/zodb>`_. (And for the
transaction system on the `transaction list
<https://groups.google.com/forum/#!forum/python-transaction>`_
<https://groups.google.com/forum/#!forum/python-transaction>`_)

Bug reporting and feature requests are submitted through github issue
trackers for various ZODB components:
Expand All @@ -70,7 +227,7 @@ trackers for various ZODB components:

- `persistent <https://github.com/zopefoundation/persistent>`_

- `transactuon <https://github.com/zopefoundation/transaction>`_
- `transaction <https://github.com/zopefoundation/transaction>`_

- `BTrees <https://github.com/zopefoundation/BTrees>`_

Expand Down

0 comments on commit ccf6a3a

Please sign in to comment.