An introductory, overview talk about PostgreSQL, given at the Database 2011 conference in January, in Israel. I point to a number of PostgreSQL features that make it a compelling choice in many different contexts.

1. PostgreSQL: So
powerful, you won’t
believe it’s open source
Reuven M. Lerner • reuven@lerner.co.il
Database 2011
January 13th, 2011

2. Who am I?
• Web developer, software architect,
consultant
• Linux Journal columnist since 1996
• Mostly Ruby on Rails + PostgreSQL, but
also Python, PHP, jQuery, and lots more...
• PostgreSQL user since (at least) 1997

3. Lots of options!
• Oracle
• Microsoft SQL Server
• IBM DB2
• MySQL
• PostgreSQL

4. How do you choose?
• Integrity (ACID compliance)
• Data types
• Functionality
• Tools
• Extensibility
• Documentation
• Community

5. PostgreSQL
• Very fast, very scalable. (Just ask Skype.)
• Amazingly flexible, easily extensible.
• Rock-solid — no crashes, corruption,
security issues for years
• Ridiculously easy administration
• It also happens to be free (MIT/BSD)

6. Brief history
• Ingres (Stonebreaker, Berkeley)
• Postgres (Stonebreaker, Berkeley)
• PostgreSQL project = Postgres + SQL
• About one major release per year
• Version 8.x — Windows port, recovery
• Version 9.0 — hot replication, upgrades

7. PostgreSQL

8. PostgreSQL

9. PostgreSQL

10. PostgreSQL

11. PostgreSQL

12. PostgreSQL

13. Data types
• Boolean
• Numeric (integer, float, decimal)
• (var)char, text (infinitely large), binary
• sequences (guaranteed unique)
• Date/time and time intervals
• IP addresses, XML, enums, arrays

14. Or create your own!

15. Or create your own!
CREATE TYPE Person AS
(first_name TEXT, last_name
TEXT);

16. Or create your own!
CREATE TYPE Person AS
(first_name TEXT, last_name
TEXT);

17. Or create your own!
CREATE TYPE Person AS
(first_name TEXT, last_name
TEXT);
CREATE TABLE Members (group_id
INTEGER, member Person);

18. PostGIS
• Some people took this all the way
• Want to include geographical information?
• No problem — we’ve got PostGIS!
• Complete GIS solution, with data types and
functions
• Keeps pace with main PostgreSQL revisions

19. Flexible internal types
• For example, text/binary storage
• Inline or in a separate table (TOAST)
• Compressed or not
ALTER TABLE Foo ALTER COLUMN
mytext SET STORAGE EXTERNAL;

20. Foreign keys that work
CREATE TABLE DVDs (id SERIAL, title TEXT, store_id
INTEGER REFERENCES Stores);
INSERT INTO DVDs (title, store_id) VALUES ('Attack of
the Killer Tomatoes', 500);

21. Foreign keys that work
CREATE TABLE DVDs (id SERIAL, title TEXT, store_id
INTEGER REFERENCES Stores);
INSERT INTO DVDs (title, store_id) VALUES ('Attack of
the Killer Tomatoes', 500);
ERROR: insert or update on table "dvds" violates
foreign key constraint "dvds_store_id_fkey"

22. Foreign keys that work
CREATE TABLE DVDs (id SERIAL, title TEXT, store_id
INTEGER REFERENCES Stores);
INSERT INTO DVDs (title, store_id) VALUES ('Attack of
the Killer Tomatoes', 500);
ERROR: insert or update on table "dvds" violates
foreign key constraint "dvds_store_id_fkey"
DETAIL: Key (store_id)=(500) is not present in table
"stores".

23. Foreign keys that work
CREATE TABLE DVDs (id SERIAL, title TEXT, store_id
INTEGER REFERENCES Stores);
INSERT INTO DVDs (title, store_id) VALUES ('Attack of
the Killer Tomatoes', 500);
ERROR: insert or update on table "dvds" violates
foreign key constraint "dvds_store_id_fkey"
DETAIL: Key (store_id)=(500) is not present in table
"stores".
ERROR: insert or update on table "dvds" violates
foreign key constraint "dvds_store_id_fkey"

24. Foreign keys that work
CREATE TABLE DVDs (id SERIAL, title TEXT, store_id
INTEGER REFERENCES Stores);
INSERT INTO DVDs (title, store_id) VALUES ('Attack of
the Killer Tomatoes', 500);
ERROR: insert or update on table "dvds" violates
foreign key constraint "dvds_store_id_fkey"
DETAIL: Key (store_id)=(500) is not present in table
"stores".
ERROR: insert or update on table "dvds" violates
foreign key constraint "dvds_store_id_fkey"
DETAIL: Key (store_id)=(500) is not present in table
"stores".

25. Custom validity checks
CREATE TABLE DVDs (id SERIAL, title
TEXT check (length(title) > 3),
store_id INTEGER REFERENCES
Stores);
INSERT INTO DVDs (title, store_id)
VALUES ('AB', 500);

26. Custom validity checks
CREATE TABLE DVDs (id SERIAL, title
TEXT check (length(title) > 3),
store_id INTEGER REFERENCES
Stores);
INSERT INTO DVDs (title, store_id)
VALUES ('AB', 500);
ERROR: new row for relation "dvds"
violates check constraint
"dvds_title_check"

27. Timestamp vs. Interval
testdb=# select now();
now
-------------------------------
2010-10-31 08:58:23.365792+02
(1 row)
Point in time
testdb=# select now() - interval '3 days';
?column?
-------------------------------
2010-10-28 08:58:28.870011+02
Difference between
(1 row) points in time

28. Built-in functions
• Math
• Text processing (including regexps)
• Date/time calculations
• Conditionals (CASE, COALESCE, NULLIF)
for use in queries
• Extensive library of geometrical functions

29. Or write your own!
• PL/pgSQL
• PL/Perl
• PL/Python
• PL/Ruby
• PL/R
• PL/Tcl

30. Triggers
• Write a function, and use it as a trigger
• The function can run before or after
inserts, deletes, or updates
• What do they do?
• Stop certain actions from happening
• Change the data before it’s really used

31. Windowing functions
• Calculate aggregate amounts on each row,
taking other rows into consideration
• For example: Rank each person’s salary
within their department

32. Smart indexing
• Functional indexes
CREATE UNIQUE INDEX on
People(lower(email_address));
• Conditional indexes
CREATE INDEX on People WHERE
is_admin = true;
• Background (concurrent) indexing

33. Transactions
• In PostgreSQL from the beginning
• Use transactions for just about anything:
BEGIN
DROP TABLE DVDs;
ROLLBACK;
SELECT * FROM DVDs; -- Works!

34. Savepoints
(or, sub-transactions)
BEGIN;
INSERT INTO table1 VALUES (1);
SAVEPOINT my_savepoint;
INSERT INTO table1 VALUES (2);
ROLLBACK TO SAVEPOINT my_savepoint;
INSERT INTO table1 VALUES (3);
COMMIT;

35. MVCC
• Readers and writers don’t block each other
• “Multi-version concurrency control”
• xmin, xmax on each tuple; rows are those
tuples with txid_current between them
• Old versions stick around until vacuumed
• Autovacuum removes even this issue

36. Full-text indexing
• Built-in, Unicode-aware full-text indexing
has been in PostgreSQL for a few years
• It’s simply a different type of index, as well
as a different search operator (@@)
• Custom dictionaries for different
languages, indicating stop words and
stemming rules

37. CTEs
• Adds a “WITH” statement, which defines a
sorta-kinda temp table
• You can then query that same temp table
• Makes many queries easier to read, write,
without a real temp table
• Better yet: CTEs can be recursive, for
everything from Fibonacci to org charts

38. WITH regional_sales AS (
SELECT region, SUM(amount) AS total_sales
FROM orders GROUP BY region
),
top_regions AS (
SELECT region FROM regional_sales
WHERE total_sales > (SELECT SUM(total_sales)/10
FROM regional_sales)
)
SELECT region,
product,
SUM(quantity) AS product_units,
SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product;

39. WITH regional_sales AS (
SELECT region, SUM(amount) AS total_sales
FROM orders GROUP BY region
),
top_regions AS (
SELECT region FROM regional_sales
WHERE total_sales > (SELECT SUM(total_sales)/10
FROM regional_sales)
)
SELECT region,
product,
SUM(quantity) AS product_units,
SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product;

40. WITH regional_sales AS (
SELECT region, SUM(amount) AS total_sales
FROM orders GROUP BY region
),
top_regions AS (
SELECT region FROM regional_sales
WHERE total_sales > (SELECT SUM(total_sales)/10
FROM regional_sales)
)
SELECT region,
product,
SUM(quantity) AS product_units,
SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product;

41. WITH regional_sales AS (
SELECT region, SUM(amount) AS total_sales
FROM orders GROUP BY region
),
top_regions AS (
SELECT region FROM regional_sales
WHERE total_sales > (SELECT SUM(total_sales)/10
FROM regional_sales)
)
SELECT region,
product,
SUM(quantity) AS product_units,
SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product;

42. WITH regional_sales AS (
SELECT region, SUM(amount) AS total_sales
FROM orders GROUP BY region
),
top_regions AS (
SELECT region FROM regional_sales
WHERE total_sales > (SELECT SUM(total_sales)/10
FROM regional_sales)
)
SELECT region,
product,
SUM(quantity) AS product_units,
SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product;

43. WITH regional_sales AS (
SELECT region, SUM(amount) AS total_sales
FROM orders GROUP BY region
),
top_regions AS (
SELECT region FROM regional_sales
WHERE total_sales > (SELECT SUM(total_sales)/10
FROM regional_sales)
)
SELECT region,
product,
SUM(quantity) AS product_units,
SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product;

44. WITH regional_sales AS (
SELECT region, SUM(amount) AS total_sales
FROM orders GROUP BY region
),
top_regions AS (
SELECT region FROM regional_sales
WHERE total_sales > (SELECT SUM(total_sales)/10
FROM regional_sales)
)
SELECT region,
product,
SUM(quantity) AS product_units,
SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product;

45. PITR
• Store WALs (write-ahead logs) to disk
• Normally, the server will apply all WALs
when it starts up
• By choosing which WALs to apply, you can
bring the database up to date until a certain
point in time

46. Streaming replication
• In 8.4, you could use “log shipping” to send
the WALs from one server to another
• When the primary server went down, you
could bring up this secondary
• In 9.0, this can happen over the network
• Faster, more reliable, and easier to
configure than previously

47. Hot standby
• In 8.4, the secondary server could not
answer queries when it was receiving WALs
from the primary
• 9.0 introduced “hot standby”: Secondary
server can answer read-only queries
• Can help with balancing certain queries

48. It’s all in the tables
• Databases are good at working with tables
• So PostgreSQL stores info in tables
• Configuration parameters
• Objects (tables, indexes, functions, etc.)
• Statistics for the optimizer
• Look through pg_catalog ... and learn!

49. Client libraries
• libpq (in C) • Java (JDBC)
• Others by 3rd • .NET (npgsql)
parties: • ODBC
• Python • JavaScript (!)
• Ruby • Just about any
language you can
• Perl imagine

50. Want to learn more?
• Mailing lists, wikis, and blogs
• All at http://postgresql.org/
• http://planetpostgresql.org
• PostgreSQL training, consulting,
development, hand-holding, and general
encouragement

51. Thanks!
(Any questions?)
reuven@lerner.co.il
http://www.lerner.co.il/
054-496-8405
“reuvenlerner” on Skype/AIM