Deploying a fault-tolerant PostgreSQL cluster on pacemaker
Corosync & pacemaker is a well known solution for creating fault-tolerant clusters. Such clusters can contain 3 working nodes or 2 working nodes and one voting-only node. The cluster can be deployed on physical or virtual servers.
This tutorial will demonstrate the process of installation and tuning of a PostgreSQL fault-tolerant cluster. You will learn that it is not so difficult as seems to be from the first glance.
Abhinav M CSG InternationalPremnath j CSG Systems International
Many businesses which use Database management systems like Oracle, DB2 & MS SQL are unreliable these days. Moreover, the costs incurred in maintaining these systems and its product licenses keeps on increasing. As the competitors are migrating over to the new technologies and tools available in the market, it is necessary for these businesses to migrate to new environment which is efficient, consistent and reliable to stay in the market and the technologies used in the current environment have become obsolete or no longer serve the business purpose. PostgreSQL has emerged as a top open-source RDBMS software. Since there is no licensing cost associated with it most of the companies are planning to migrate the databases which are currently running on other RDBMS like Oracle, DB2, MS SQL server to PostgreSQL. This report summarizes the various methodologies, procedures and techniques involved in successfully migrating the data from Oracle to PostgreSQL & DB2 to PostgreSQL. Migration is not a simple effort there should be proper planning and testing involved in this right from database connectivity to performance analysis. In this paper we are going to cover most of the steps which we need to consider before the migration and after the migration like choosing the correct tools for implementing the migration, time taken to migrate ,data compatibility, code conversion, application connectivity to database, database configuration parameters, performance analysis, replication setups, database monitoring, patching and backup strategies.
Алексей Лесовский PostgreSQL Consulting LLC
Today no one is surprised by cloud infrastructure anymore, but not all its components are easy to deploy in cloud. For example, the database is always very demanding in terms of performance and resources. Scaling and fault tolerance are the most acute problems, that's why we have been observing rapid development of alternative DBMS in the recent years. However, traditional relational DBMS have already accumulated a lot of various features, so they often remain the first choice. Besides, they are constantly evolving and offer a wide variety of scaling tools. I will mainly speak about PostgreSQL, when you should consider scaling, and how to do it right.
We will touch upon the following topics:
- Streaming replication and balancing read/write workloads
- Logical replication and data sharding
- High availability and fault tolerance
This talk should be interesting to DBAs, system administrators, team leads, infrastructure architects, as well as wider audience dealing with PostgreSQL.
OOleksii Kozlov Swarm64 ASMikhail Tsvetkov Intel
If you care about Postgres performance, there are a number of hardware acceleration options to help with different use cases. Intel Optane DC persistent memory creates new tier in data hierarchy allowing developers to utilize performance of traditional memory combining with volume and persistency of block storage devices. Unlike traditional DRAM-only in-memory systems, where memory is small, expensive, and volatile, Intel Optane DC persistent memory makes it possible to run larger Postgres databases (terabytes) in memory for higher performance. FPGAs are integrated circuits that can be reprogrammed dynamically to accelerate a specific workload such as SQL execution and data compression. FPGA accelerators extend Postgres with hundreds of SQL reader and writer processes that work in parallel on the FPGA. It’s similar to adding hundreds new cores to boost parallel processing on your server.
Bruce Momjian EnterpriseDB
Postgres has always had strong support for relational storage. However, there are many cases where relational storage is either inefficient or overly restrictive. This talk shows the many ways that Postgres has expanded to support non-relational storage, specifically the ability to store and index multiple values, even unrelated ones, in a single database field. Such storage allows for greater efficiency and access simplicity, and can also avoid the negatives of entity-attribute-value (eav) storage. The talk will cover many examples of multiple-value-per-field storage, including arrays, range types, geometry, full text search, xml, json, and records.