Postgres has the unique ability to act as a powerful data aggregator in many data centers. This presentation shows how Postgres's extensibility, access to foreign data sources, and ability handle NoSQL-like and data warehousing workloads gives it unmatched capabilities to function in this role.

1. Making Postgres Central in Your Data Center
BRUCE MOMJIAN
February, 2014
This talk explores why Postgres is uniquely capable of functioning
as a central database in enterprises. Title concept from Josh Berkus
Creative Commons Attribution License http://momjian.us/presentations
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2. Outline
1. Object-Relational (extensibility)
2. NoSQL
3. Data analytics
4. Foreign data wrappers (database federation)
5. Central role
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3. 1. Object-Relational (Extensibility)
Object-relational databases like Postgres support support classes
and inheritance, but most importantly, they define database
functionality as objects that can be easily manipulated.
http://en.wikipedia.org/wiki/Object-relational_database
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4. How Is this Accomplished?
starelid
staattnum
staop
pg_statistic
oprleft
oprright
oprresult
oprcom
oprnegate
oprlsortop
oprrsortop
oprcode
oprrest
oprjoin
pg_operator
typrelid
typelem
typinput
typoutput
typbasetype
pg_type
prolang
prorettype
pg_proc
pg_rewrite
ev_class
datlastsysoid
pg_database
tgfoid
tgrelid
pg_trigger
inhrelid
pg_inherits
inhparent
pg_language
pg_namespacepg_depend pg_shadow
pg_aggregate
aggfinalfn
aggtransfn
aggfnoid
aggtranstype
castsource
casttarget
pg_cast
castfunc
pg_description
pg_constraint
contypid
pg_conversion
conproc
amopopr
amopclaid
pg_attribute
indexrelid
attnum
amopclaid
atttypid
indrelid
pg_attrdef
pg_group
adrelid
pg_index
adnum
pg_am
pg_amop
amgettuple
reltoastidxid
aminsert
reltoastrelid amcostestimate
amproc
ambeginscan
pg_amproc
amrescan
relfilenode
amendscan
relam
ammarkpos
reltype amrestrpos
pg_class
ambuild
opcdeftype
ambulkdelete
pg_opclass
attrelid
http://www.postgresql.org/docs/current/static/catalogs.html
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5. Example: ISBN Data Type
CREATE EXTENSION isn;
dT
List of data types
Schema | Name | Description
--------+--------+--------------------------------------------------
public | ean13 | International European Article Number (EAN13)
public | isbn | International Standard Book Number (ISBN)
public | isbn13 | International Standard Book Number 13 (ISBN13)
public | ismn | International Standard Music Number (ISMN)
public | ismn13 | International Standard Music Number 13 (ISMN13)
public | issn | International Standard Serial Number (ISSN)
public | issn13 | International Standard Serial Number 13 (ISSN13)
public | upc | Universal Product Code (UPC)
http://www.postgresql.org/docs/current/static/isn.html
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6. ISBN Behaves Just Like Built-In Types
dTS
…
pg_catalog | integer | -2 billion to 2 billion integer, 4-byte storage
…
public | isbn | International Standard Book Number (ISBN)
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7. The System Catalog Entry for INTEGER
SELECT * FROM pg_type WHERE typname = ’int4’;
-[ RECORD 1 ]--+---------
typname | int4
typnamespace | 11
typowner | 10
typlen | 4
typbyval | t
typtype | b
typcategory | N
typispreferred | f
typisdefined | t
typdelim | ,
typrelid | 0
typelem | 0
typarray | 1007
typinput | int4in
typoutput | int4out
typreceive | int4recv
typsend | int4send
typmodin | -
typmodout | -
typanalyze | -
typalign | i
typstorage | p
typnotnull | f Making Postgres Central in Your Data Center 7 / 38

8. The System Catalog Entry for ISBN
SELECT * FROM pg_type WHERE typname = ’isbn’;
-[ RECORD 1 ]--+---------------
typname | isbn
typnamespace | 2200
typowner | 10
typlen | 8
typbyval | t
typtype | b
typcategory | U
typispreferred | f
typisdefined | t
typdelim | ,
typrelid | 0
typelem | 0
typarray | 16405
typinput | isbn_in
typoutput | public.isn_out
typreceive | -
typsend | -
typmodin | -
typmodout | -
typanalyze | -
typalign | d
typstorage | p
typnotnull | f Making Postgres Central in Your Data Center 8 / 38

9. Not Just Data Types, Languages
CREATE EXTENSION plpythonu;
dL
List of languages
Name | Owner | Trusted | Description
-----------+----------+---------+------------------------------------------
plpgsql | postgres | t | PL/pgSQL procedural language
plpythonu | postgres | f | PL/PythonU untrusted procedural language
http://www.postgresql.org/docs/current/static/plpython.html
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10. Available Languages
◮ PL/Java
◮ PL/Perl
◮ PL/pgSQL (like PL/SQL)
◮ PL/PHP
◮ PL/Python.
◮ PL/R (like SPSS)
◮ PL/Ruby
◮ PL/Scheme
◮ PL/sh
◮ PL/Tcl
◮ SPI (C)
http://www.postgresql.org/docs/current/static/external-pl.html
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11. Specialized Indexing Methods
◮ BTree
◮ Hash
◮ GiST (generalized search tree)
◮ SP-GiST (space-partitioned GiST)
◮ GIN (generalized inverted index)
http://www.postgresql.org/docs/current/static/indexam.html
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12. Index Types Are Defined in the System Catalogs Too
SELECT amname FROM pg_am;
amname
--------
btree
hash
gist
gin
spgist
http://www.postgresql.org/docs/current/static/catalog-pg-am.html
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13. Operators Have Similar Flexibility
Operators are function calls with left and right operators of specified types:
doS
Schema | Name | Left arg type | Right arg type | Result type | Description
…
pg_catalog | + | integer | integer | integer | add
dfS
Schema | Name | Result data type | Argument data types | Type
…
pg_catalog | int4pl | integer | integer, integer | normal
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14. Other Extensibility
◮ Casts are defined in pg_cast, int4(float8)
◮ Aggregates are defined in pg_aggregate, sum(int4)
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15. Externally Developed Plug-Ins
◮ PostGIS (Geographical Information System)
◮ PL/v8 (server-side JavaScript)
◮ experimentation, e.g. full text search was originally
externally developed
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16. Offshoots of Postgres
◮ AsterDB
◮ Greenplum
◮ Informix
◮ Netezza
◮ ParAccel
◮ Postgres XC
◮ Redshift (Amazon)
◮ Truviso
◮ Vertica
◮ Yahoo! Everest
https://wiki.postgresql.org/wiki/PostgreSQL_derived_databases
http://de.slideshare.net/pgconf/elephant-roads-a-tour-of-postgres-forks
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17. Offshoots of Postgres
https://raw.github.com/daamien/artwork/master/inkscape/PostgreSQL_timeline/timeline_postgresql.png
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18. Plug-In Is Not a Bad Word
Many databases treat extensions as special cases, with serious
limitations. Postgres built-ins use the same API as extensions, so ll
extensions operate just like built-in functionality.
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19. Extensions and Built-In Facilities
Behave the Same
Extensions
PL/R
ISN
PostGIS
Postgres System Tables
int4
btree
sum()
PL/pgSQL
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20. 2. NoSQL
SQL
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21. NoSQL Types
There is no single NoSQL technology. They all take different
approaches and have different features and drawbacks:
◮ Key-Value stores, e.g. Redis
◮ Document databases, e.g. MongoDB (JSON)
◮ Columnar stores: Cassandra
◮ Graph databases: Neo4j
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22. Why NoSQL Exists
Generally, NoSQL provides fast querying, auto-sharding, and
flexible schemas by avoiding:
◮ A powerful query language
◮ A sophisticated query optimizer
◮ Data normalization
◮ Joins
◮ Referential integrity
◮ Durability
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23. Are These Drawbacks Worth the Cost?
◮ Difficult Reporting Data must be brought to the client for
analysis, e.g. no aggregates or data analysis functions.
Schema-less data requires complex client-side knowledge for
processing
◮ Complex Application Design Without powerful query
language and query optimizer, the client software is
responsible for efficiently accessing data and for data
consistency
◮ Durability Administrators are responsible for data retention
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24. When Should NoSQL Be Used?
◮ Massive write scaling is required, more than a single server
can provide
◮ Only simple data access pattern is required
◮ Additional resources allocation for development is acceptable
◮ Strong data retention or transactional guarantees are not
required
◮ Unstructured duplicate data that greatly benefits from
column compression
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25. When Should Relational Storage Be Used?
◮ Easy administration
◮ Variable workloads and reporting
◮ Simplified application development
◮ Strong data retention
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26. The Best of Both Worlds: Postgres
Postgres has many NoSQL features without the drawbacks:
◮ Schema-less data types, with sophisticated indexing support
◮ Transactional schema changes with rapid additional and
removal of columns
◮ Durability by default, but controllable per-table or
per-transaction
◮ Postgres XC and PL/Proxy allow auto-sharding for write
scaling
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27. Schema-Less Data: JSON
CREATE TABLE customer (id SERIAL, data JSON);
INSERT INTO customer VALUES (DEFAULT, ’{"name" : "Bill", "age" : 21}’);
SELECT data->’name’ FROM customer WHERE (data->’age’)::text = ’21’;
?column?
----------
"Bill"
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28. Easy Relational Schema Changes
ALTER TABLE customer ADD COLUMN status CHAR(1);
BEGIN WORK;
ALTER TABLE customer ADD COLUMN debt_limit NUMERIC(10,2);
ALTER TABLE customer ADD COLUMN creation_date TIMESTAMP WITH TIME ZONE;
ALTER TABLE customer RENAME TO cust;
COMMIT;
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29. 3. Data Analytics
◮ Aggregates
◮ Optimizer
◮ Server-side languages, e.g. PL/R
◮ Window functions
◮ Bitmap heap scans
◮ Tablespaces
◮ Data partitioning
◮ Materialized views
◮ Common (recursive) table expressions
◮ Min/Max indexes (coming in 2015)
Data warehouse-specific solutions are required for parallel
operations across servers.
http://www.slideshare.net/PGExperts/really-big-elephants-postgresql-dw-15833438
http://wiki.postgresql.org/images/3/38/PGDay2009-EN-Datawarehousing_with_PostgreSQL.pdf
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30. Read-Only Slaves for Analytics
Network
Data WarehouseMaster Server
/pg_xlog/pg_xlog
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31. 4. Foreign Data Wrappers (Database Federation)
Foreign data wrappers (SQL MED) allow queries to read and write
data to foreign data sources. Foreign database support includes:
◮ CouchDB
◮ Informix
◮ MongoDB
◮ MySQL
◮ Neo4j
◮ Oracle
◮ Postgres
◮ Redis
The transfer of joins, aggregates, and sorts to foreign servers is not yet
implemented.
http://www.postgresql.org/docs/current/static/ddl-foreign-data.html
http://wiki.postgresql.org/wiki/Foreign_data_wrappers
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32. Foreign Data Wrappers to Interfaces
◮ JDBC
◮ LDAP
◮ ODBC
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33. Foreign Data Wrappers to
Non-Traditional Data Sources
◮ Files
◮ HTTP
◮ AWS S3
◮ Twitter
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34. Foreign Data Wrapper Example
CREATE SERVER postgres_fdw_test
FOREIGN DATA WRAPPER postgres_fdw
OPTIONS (host ’localhost’, dbname ’fdw_test’);
CREATE USER MAPPING FOR PUBLIC
SERVER postgres_fdw_test
OPTIONS (password ’’);
CREATE FOREIGN TABLE other_world (greeting TEXT)
SERVER postgres_fdw_test
OPTIONS (table_name ’world’);
det
List of foreign tables
Schema | Table | Server
--------+-------------+-------------------
public | other_world | postgres_fdw_test
(1 row)
Foreign Postgres server name in red; foreign table name in blue
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35. Read and Read/Write Data Sources
Postgres
ora_tab
tw_tab
mon_tab
MongoDB
Twitter
Oracle
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36. 5. Postgres Centrality
Postgres can rightly take a central place in the data center with
its:
◮ Object-Relation flexibility and extensibility
◮ NoSQL-like workloads
◮ Powerful data analytics capabilities
◮ Access to foreign data sources
No other database has all of these key components.
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37. Postgres’s Central Role
Extensions
NoSQL
Postgres
Warehouse
Data
Foreign Data
Wrappers
Window Functions
Data Paritioning
Bitmap Scans Sharding
Oracle
Twitter
MongoDB
Easy DDL
JSON
PL/R
ISN
PostGIS
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38. Conclusion
http://momjian.us/presentations http://flickr.com/photos/vpickering/3617513255
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