GridSQL is an open source distributed database built on PostgreSQL that allows it to scale horizontally across multiple servers by partitioning and distributing data and queries. It provides significantly improved performance over a single PostgreSQL instance for large datasets and queries by parallelizing processing across nodes. However, it has some limitations compared to PostgreSQL such as lack of support for advanced SQL features, slower transactions, and need for downtime to add nodes.

3. Founder of Cirrus Technologies

4. Former Chief Architect of EnterpriseDB

6. Architecture

7. Query Flow

8. Scaling

9. Limitations

11. Greenplum, Netezza or Teradata

13. Not just “Read-Only”, can execute UPDATE, DELETE

14. Data Loader for parallel loading

15. Standard connectivity via PostgreSQL compatible connectors: JDBC, ODBC, ADO.NET, libpq (psql)

17. A high availability solution like Streaming Replication in PostgreSQL 9.0

18. A scalable transactional solution like PostgresXC

19. An elastic, eventually consistent NoSQL database

23. Since each subtable is also partitioned across nodes, they are scanned in parallel

24. Queries execute much faster

28. Agents

30. Looks for joins between tables on partitioned columns

32. Like groups of intermediate results shipped to same target node

33. Second aggregation done in parallel

34. Coordinator streams in node results, combining on the fly and sending to client result set, performing a merge sort if ORDER BY present

37. SUM2 (SUM(stat1)) / SUM2 (COUNT(stat1))

41. Query 1 – Execution (no Agents) Go to Animation Slide

43. Query 7 – Execution (with Agents) Go to Animation Slide

49. No Stored Procedures

50. No Full Text Search

51. No Spatial

53. All partitioned rows must be hashed to be mapped to the proper node

57. Backup each node separately

60. The results are dependent on the cloud vendor

62. GridSQL can scale linearly as more nodes are added

63. GridSQL is open source so if the limitations are an issue,

64. submit a patch