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Empowering businesses with high-performance, scalable PostgreSQL solutions
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Articles by Umair
Contributions
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Your database performance is plummeting due to deadlocks. How do you resolve them effectively?
- Take a look at the transaction isolation level and make sure that it isn't set to a very strict level - Application design can contribute to increased deadlocks. Look at what is causing the deadlock and redesign application queries if possible
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Managing database upgrades is stressful. How can you keep your team motivated through it all?
I think one of the best ways to maintain motivation levels is to translate the efforts into the long term benefits to, not only the organization, but to the personnel responsible. Getting an upgrade means getting new features, improving reliability, and overall getting more done with less. The stakeholders are directly impacted by these benefits and keeping that in view all the time is important.
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Your critical database system is down due to a power outage. How do you bring it back online efficiently?
Well, if the power is down and there is no backup, there isn't much you can do till you get power back. Hence, this is a classic case where PREEMPTIVE actions are required. 1. Ensure you have a replica that is physically separate from your primary database. The replica adds redundancy and ensures that in case the primary goes down, you have something to fall back on. 2. Take periodic backups and store them at a different location than your database. In case the database goes down, you can restore from your backup. It is important to periodically test your backups as well.
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Facing database performance degradation, how can you optimize without adding downtime?
Focus on the following 4 areas, in order of priority: 1. Query and SQL optimization - Look at the top 3 longest running and the top 3 most frequently run queries and optimize them. 2. Leveraging performance features of your database - Understand features like indexing, partitioning, & parallelization to leverage them to the fullest. 3. Architectural improvements - Putting too much load on a single table or a single database can use problems. Try and architect the structure to distribute the load to speed up the entire system. 4. Parameter tuning - Study your workload and available hardware resources and then tune database configuration parameters accordingly to get the maximum from what you have.
Activity
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Does your business rely on PostgreSQL and you need to optimize its performance or scale effectively? Managing PostgreSQL databases can involve…
Does your business rely on PostgreSQL and you need to optimize its performance or scale effectively? Managing PostgreSQL databases can involve…
Shared by Umair Shahid
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Continuing with the series of transitioning from Oracle to PostgreSQL ... The process of managing roles and privileges in a database is about…
Continuing with the series of transitioning from Oracle to PostgreSQL ... The process of managing roles and privileges in a database is about…
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Setting up a PostgreSQL cluster shouldn’t feel like scaling Everest. (If you are managing data infrastructure, this one’s for you.) Every database…
Setting up a PostgreSQL cluster shouldn’t feel like scaling Everest. (If you are managing data infrastructure, this one’s for you.) Every database…
Shared by Umair Shahid
Experience
Education
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Ghulam Ishaq Khan Institute of Engineering Sciences and Technology
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Activities and Societies: Sports coordinator, Volleyball team, Basketball team, General Secretary - ACM GIKI chapter
Volunteer Experience
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Chair
PostgreSQL Global Development Group
- 1 year
Science and Technology
Chair, Code of Conduct Committee
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Member Core Committee
Khud-Kafeel Trust
- 4 years 1 month
Economic Empowerment
Khud-kafeel trust is an informal group of individuals that provides micro financing opportunities for the poorest of the poor in our society.
- Stepped in to create structure around an existing ad hoc group of volunteers
- Created various functional roles within the committee
- Spearheading the fund drive to maximize inflow of donations
Publications
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Benchmark Study on Replication Lag in PostgreSQL using Single Region and Multi-Region Architectures
Stormatics
In today’s increasingly distributed environments, ensuring low replication lag is critical for maintaining performance and availability in database systems.
Our latest whitepaper, “Benchmark Study on Replication Lag in PostgreSQL using Single Region and Multi-Region Architectures”, explores the behavior of PostgreSQL clusters and factors impacting replication lag under different configurations and workloads.
This study provides a detailed comparison between a single-region…In today’s increasingly distributed environments, ensuring low replication lag is critical for maintaining performance and availability in database systems.
Our latest whitepaper, “Benchmark Study on Replication Lag in PostgreSQL using Single Region and Multi-Region Architectures”, explores the behavior of PostgreSQL clusters and factors impacting replication lag under different configurations and workloads.
This study provides a detailed comparison between a single-region, single-active node setup and a multi-region active-active architecture, measuring the impact of replication lag in real-world scenarios. Utilizing pgbench and HammerDB as benchmarks, we conducted load tests to assess how well PostgreSQL Distributed (PGD) handles replication in both setups. The findings reveal key insights into performance under various conditions, offering valuable recommendations for anyone managing PostgreSQL in distributed environments.
Key Highlights:
• Replication Lag Analysis: Comparison of single-region vs. multi-region architectures.
• Performance Benchmarks: Results under varying load conditions using pgbench and HammerDB.
• Real-World Implications: Insights into the challenges and benefits of distributed PostgreSQL clusters.
• Recommendations: Best practices for minimizing replication lag based on your environment’s architecture.
Whether you manage a local high-performance database or a globally distributed system, this whitepaper provides actionable insights to optimize your PostgreSQL clusters for better performance and reliability. -
Transparent Data Encryption and High Availability
Stormatics
Transparent Data Encryption (TDE) is an essential requirement for businesses handling sensitive data, whether personal or financial.
However, there are implications for backups and auto-failover. Without central storage of the encryption key with tight access controls, backups are useless and the server will not be able to start automatically after a failover.
The interaction between these components is not always intuitive. This paper is dedicated to clarifying these…Transparent Data Encryption (TDE) is an essential requirement for businesses handling sensitive data, whether personal or financial.
However, there are implications for backups and auto-failover. Without central storage of the encryption key with tight access controls, backups are useless and the server will not be able to start automatically after a failover.
The interaction between these components is not always intuitive. This paper is dedicated to clarifying these interactions.
Key highlights include:
- Overview of High Availability (HA) and TDE
- Operational challenges associated with running HA and TDE simultaneously
- Recommendations to be considered for both infrastructures
- Processes to be documented, tested, and rehearsed.Other authorsSee publication -
Data Ingestion Benchmark Comparison between PostgreSQL and MongoDB
Stormatics
Choosing between PostgreSQL and MongoDB is highly dependent on the unique requirements of your business. However, there are factors such as data complexity, query patterns, and the importance of features like indexing and data integrity that should be considered while making the decision.
To understand the extent of their capabilities, we conducted an extensive study to examine the data insertion performance in both PostgreSQL and MongoDB especially to examine the utilization of their…Choosing between PostgreSQL and MongoDB is highly dependent on the unique requirements of your business. However, there are factors such as data complexity, query patterns, and the importance of features like indexing and data integrity that should be considered while making the decision.
To understand the extent of their capabilities, we conducted an extensive study to examine the data insertion performance in both PostgreSQL and MongoDB especially to examine the utilization of their respective JSONB and BSON data types.
We identified strengths and challenges inherent to each database and offered practical insights for optimal utilization based on:
- Versatility and Reliability
- Scalability and Growth
- Considerations for Use Cases
- Application-Specific Decision Making
This study uncovered nuanced insights into the performance dynamics of both databases across various benchmarks. You can learn more in detail by downloading the whitepaper.Other authorsSee publication
Languages
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English
Native or bilingual proficiency
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Urdu
Native or bilingual proficiency
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Punjabi
Native or bilingual proficiency
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