Dear PostgreSQL Community, We are implementing a new feature in our application that is expected to generate a significant amount of data, and we are seeking your expert guidance on how to best handle this growth within our existing PostgreSQL setup.
Currently, our PostgreSQL instance runs on an EC2 c5.4xlarge Ubuntu instance with the following specifications: - *RAM:* 32 GB - *Disk:* 1.2 TB - *vCPUs:* 16 Our database architecture utilizes a primary-standby streaming replication setup. Application modules (running in Kubernetes pods) connect to the database through Pgpool-II, using HikariCP for connection pooling. We have multiple databases on our primary server, with their approximate current sizes as follows: - *C:* 620 GB - *M:* 225 GB - *P:* 59 GB - *K:* 13 MB The total current size of our databases is around *1 TB*. With the new feature, we anticipate a substantial increase in data, potentially reaching *10 TB* over the next 5-7 years. Below is the table for current size and expected growth in size: *S.No.* *DB* *Current DB size* *Future DB size* *Schema Name* *Current Schema size* *Future Schema size * 1 C 1 TB 8 TB - 10 TB acc 297 GB 3 TB - 4 TB po 270 GB 2.6 TB - 3.5 TB pa 27 GB 270 GB pra 13 GB 130 GB fu 13 GB 130 GB te 167 MB 2 GB pro 30 MB 300 MB 2 M 225 GB 2.2 TB - 3 TB bi 82 GB 820 GB co 80 GB 800 GB ps 17 GB 170 GB qo 16 GB 160 GB to 7 GB 70 GB in 7 GB 70 GB di 6 GB 60 GB no 4 GB 40 GB do 4 GB 40 GB cl 3 GB 30 GB 3 P 60 GB 600 GB au 45 GB 450 GB fi 8 GB 80 GB con 4 GB 40 GB ba 1 GB 10 GB li 2 MB 20 GB We would greatly appreciate your insights on the following points: 1. *Scalability for Large Datasets:* Conceptually, PostgreSQL is known to handle large datasets. However, we'd like to confirm if a single PostgreSQL instance can realistically and efficiently manage 10-12 TB of data in a production environment, considering typical transaction loads. 2. *Database Split Strategy:* Our largest database, "C," currently occupies 620 GB. It contains multiple schemas. We are considering splitting database "C" into two new databases: "C1" to exclusively house the "acc" schema, and "C2" for the remaining schemas. Is this a recommended approach for managing growth, and what are the potential pros and cons? 3. *Server Allocation for Split Databases:* If we proceed with splitting "C" into "C1" and "C2," would it be advisable to assign a new, separate database server for "C2," or could both "C1" and "C2" reside on the same database server? What factors should we consider in making this decision? 4. *Performance Limits per Database and Database Server:* From a performance perspective, is there a general "limit" or best practice for the maximum amount of data a single database server should handle (e.g., 10 TB) and similarly general limit per database? How does this influence the decision to add more database servers? 5. *Best Practices for Large-Scale Data Management:* Beyond standard practices like indexing and partitioning, what other best practices should we consider implementing to ensure optimal performance and manageability with such a large dataset? This could include configurations, maintenance strategies, etc. 6. *Hardware Configuration Recommendations:* Based on our projected data growth and desired performance, what hardware configurations (e.g., RAM, CPU, storage I/O, storage type like NVMe) would you recommend for future database servers to efficiently handle 10-12 TB? 7. *Open-Source Horizontal Scaling Solutions:* Are there any open-source horizontal scaling solutions for PostgreSQL (other than Citus Data) that the community recommends or has experience with for managing extremely large datasets? Any pointers or guidance on this would be highly valuable. Thank you in advance for your time and expertise. We look forward to your valuable insights. Thanks & Regards, Ramzy
