Introduction:
My name is Hettie Dombrovskaya, and I has been doing databases and data management since the very beginning of my professional career, which is now forty-two years long! You can say, I started doing databases even before databases. I graduated with BS in CS in 1985 from the University of Saint Petersburg, and received a PhD in CS from the same University in 1995. Although I was exposed to the University Postgres in the early 1990s, I didn’t use Postgres on industrial scale until 2011. By that time, I worked with five major databases, strongly preferring Oracle, and I was sure that Postgres was something I was going to do “temporarily.” Yet, three months later, I fall in love with Postgres and never looked back. My current role in the Postgres community is to run around and tell people what’s wrong with Postgres and how we can make it better. On a more serious note, I frequently speak at Postgres conferences and organize training sessions. For the past three years, I was an organizer of PG Day Chicago, and I ran Chicago PostgreSQL User Group for nine years. Last year, together with Dian Fay and Anna Bailliekova, I founded Prairie Postgres NFP – a recognized Postgres NPO, serving Midwest States of the USA. We focus on growing local Postgres community and outreach to software engineers and academia. Former Chicago PUG is rebranded as Illinois PostgreSQL User Group, and we just announced PG DATA 2026: a new Postgres Conference in Chicago.
Journey in PostgreSQL:
As I mentioned, I was all about databases from the start of my career, and was exposed to many DBMSs in the 1980s- 1990s, including writing a simple database on Perl for one of the Open Source project. Being a university researcher, I dipped my toe into University Postgres in 1990s, but I considered it being a purely academic exercise. Everything changed in 2011, when I got a job as Postgres DBA knowing nothing about it. The hiring manager told me: we know that you do not know Postgres, but to be honest, nobody knows Postgres. We know you are a good DBA, and that’s enough. As I learned later, that was very far from the truth – Postgres appeared to be drastically different from anything I knew before, but once started, I could not think about going back.
Can you share a pivotal moment or project in your PostgreSQL career that has been particularly meaningful to you?
Each new project I ever started was meaningful in terms I learned something new and tried things I never tried before, but the most meaningful by far was my work at Braviant Holdings. By the time I started at Braviant, I already had a well-recognized name, but I never was in a position where I was literally “in charge of everything.” I was the sixth company employee, and the first and only IT person for some time, and from day one, I had to make important technical decisions, which would define the company’s future development. That was the first time in my career when I had nobody backing me up. I had to take full responsibility for my decisions, and I realized that I like it, that it’s not “just job,” but way more than that.
Contributions and Achievements:
I support several projects, all of them can be found in my GitHub repo https://github.com/hettie-d. pg_bitemporal is a set of functions which implement AVF – asserted versioning framework, otherwise called dimensional time. I hope that Postgres will incorporate these features into its core soon, and I will be able to retire it. NORM is a framework which can be used by application developers instead of ORMs, supporting bulk operations and transferring complex nested objects between Postgres database and Object-oriented applications. And lastly, my most popular project which I consider my biggest contribution, is postgres_air – the largest publicly-available Postgres training database. We developed the first version of this database together with Boris Novikov when we worked on the first edition of “PostgreSQL Query Optimization” book. We wanted to build real-world examples for the book, and we realized that there was no publicly available database that would be large enough to illustrate the optimization concepts.
Have you faced any challenges in your work with PostgreSQL, and how did you overcome them?
The biggest challenge was my first encounter with Postgres. As I mentioned, I already had twenty-eight years of database experience, fifteen of them being with Oracle. I was sure I know everything about databases, and if I can optimize queries and applications in Oracle, no other database would be a problem. I appeared to be very far from the truth. I was shocked to find out that almost nothing from my previous knowledge was applicable, and things didn’t work with Postgres how they worked with Oracle. Remembering how I learned to tame Postgres the hard way, i want to make sure that other newcomers have less traumatic experience. That was one of the biggest drivers for PostgreSQL Query Optimization book.
Community Involvement:
Postgres community is the most exciting and most valuable part of Postgres. That was one of the first things I found about Postgres, and that’s what I like the most: hundreds of people ready to help! My community involvement is listed in the intro, copying it here for consistency. For the past three years, I was an organizer of PG Day Chicago, and I ran Chicago PostgreSQL User Group for nine years. Last year, together with Dian Fay and Anna Bailliekova, we founded Prairie Postgres NFP (https://prairiepostgres.org/)- a recognized Postgres NPO, serving Midwest States of the USA. We focus on growing local Postgres community and outreach to software engineers and academia. Former Chicago PUG is rebranded Illinois PostgreSQL User Group, and we just announced PG DATA 2026(2026.pg-data.org) a new Postgres Conference in Chicago.
Can you share your experience with mentoring or supporting other women in the PostgreSQL ecosystem?
I believe that the most critical part of supporting women as well as other underrepresented groups is the outreach. It is not enough to say: please reach out if you need support. It is important to make the first move. Sadly, there are multiple stereotypes regarding the women’s role in IT. For example, I remember heading to a company-wide meeting in a big company, where not everyone knew everyone. During the brief introductions on the way to the meeting, somebody asked me and two other women: and you are QA, aren’t you? Unfortunately, many women fall into the same stereotype the tech society imposes, and believe that a woman in IT can only be a QA engineer, or a scrum master, or a PM. I try to reach out to women who never considered the knowledge of Postgres being an assert, and I invite them to attend conferences. I encourage women to submit their proposals to Postgres conferences, even when they never tried it before. I am always happy to do a mock interview, or to listen to a presentation dry run. It’s not enough to say “you are doing great!” Constructive criticism is vital for professional development.
.Insights and Advice:
I have a blog post about it: https://hdombrovskaya.wordpress.com/2025/01/29/career-success-in-tech-as-a-single-mother-forget-the-stereotypesaa-copy-of-my-post-on-elpha/
Feel free to copy or share the whole post
Are there any resources (books, courses, forums) you’d recommend to someone looking to deepen their PostgreSQL knowledge?
I can use an opportunity for a shameless self-promotion here: https://www.amazon.com/PostgreSQL-Query-Optimization-Ultimate-Efficient/dp/B0CK5GWWQ1
Jimmy Angelakos book “PostgreSQL Mistakes and How to Avoid Them” is about to be published my Manning Publications. I was a technical reviewer for this book, and I can’t say enough about how great this book is! For application developers, I highly recommend High Performance PostgreSQL for Rails by Andrew Atkinson: https://www.amazon.com/High-Performance-PostgreSQL-Rails-Maintainable/dp/B0CX876RLY
Most importantly, attend conferences, read blogs, participate in your local meetups! And don’t hesitate to ask!
.Looking Forward:
For the upcoming Postgres 18, I am mostly excited about the first portion of temporal tables support finally making it into Postgres core! Also, as usual, I am excited about multiple performance improvements. In the future, I am really looking forward for yet better support of partitions. Also, I hope to convince somebody that Postgres needs packages!
Do you have any upcoming projects or goals within the PostgreSQL community that you can share?
Since October 2024, my focus in my community activities has been growing Prairie Postgres. I hope to build Postgres community in the Greater Midwest, to have several PostgreSQL User Groups in the neighboring states, not just in Chicago!
Personal Reflection:
PostgreSQL community literally made me the person I am now. Just to think that I could never dive into Postgres, and continue to be an Oracle DBA! I wouldn’t even know how much I missed! I can only compare the importance of Postgres to the importance of my move to the USA: if I wouldn’t move, I would never know what I missed. Working with Postgres and being a part of Postgres community sparked innovation and creativity in me like nothing else. The support I always had from the community at large was vital for my professional growth.
How do you balance your professional and personal life, especially in a field that is constantly evolving?
I like the phrase I first heard from Dr. Sun “There is no work-life balance, it is work-life integration”. More in the article I shared above.
Message to the Community:
When I attended my first Postgres Conference in 2012, i felt intimidated. I didn’t understand most of the talks, and I felt that everyone around me knew tons more than I. So, my message is the following: if you feel similarly, you are not alone! It’s OK to feel like that. Two years later, I came to a conference check-in, and everyone knew me by name, and I was wondering when did this transformation happen. Listen. Ask questions. Don’t be afraid to ask “a dumb question,” and don’t pretend you understand something if you didn’t. Ask to explain. Nobody will laugh at you, and you will learn something.
In PostgreSQL, table bloat can negatively impact performance by increasing storage requirements and slowing down queries. pg_squeeze is a powerful tool designed to combat this issue by automatically reorganizing tables to reclaim wasted space without requiring downtime. This talk will explore the mechanics of table bloat in PostgreSQL, introduce the capabilities of pg_squeeze, and demonstrate how it helps maintain optimal database performance by performing non-blocking vacuum operations and table maintenance. Attendees will gain insights into how to integrate and configure pg_squeeze in their environments and learn about its advantages over traditional methods like VACUUM FULL. Whether you’re managing a busy production database or looking to improve PostgreSQL performance, this session will provide practical strategies to tackle table bloat effectively.
Features of postgres 17
Our idea explores the implementation of AI-driven query optimization in PostgreSQL, addressing the limitations of traditional optimization methods in handling modern database complexities. We present an innovative approach using reinforcement learning for automated index selection and query plan optimization. Our system leverages PostgreSQL’s pg_stat_statements for collecting query metrics and employs HypoPG for index simulation, while a neural network model learns optimal indexing strategies from historical query patterns. Through comprehensive testing on various workload scenarios, we will validate the model’s ability to adapt to dynamic query patterns and complex analytical workloads. The research also examines the scalability challenges and practical considerations of implementing AI optimization in production environments.
Our findings establish a foundation for future developments in self-tuning databases while offering immediate practical benefits for PostgreSQL deployments. This work contributes to the broader evolution of database management systems, highlighting the potential of AI in creating more efficient and adaptive query optimization solutions.
In this talk, we will explore the emerging capabilities of vector search and how PostgreSQL, with its pgvector extension, is revolutionizing data retrieval by supporting AI/ML-powered vector-based indexing and search. As machine learning models generate high-dimensional vector embeddings, the need for efficient similarity searches has become critical in applications such as recommendation systems, image recognition, and natural language processing. |
This tech talk delves into the critical world of PostgreSQL query plans, providing attendees with the knowledge and tools to understand, analyze, and optimize their database queries. We’ll begin by defining query plans and emphasizing their crucial role in database performance. We’ll explore the inner workings of the PostgreSQL planner, examining how it leverages various optimization techniques like sequential scans, index scans, joins algorithms (hash join, merge join, nested loop), and more to craft the most efficient execution strategy for a given query.
The core of the talk focuses on practical analysis. Attendees will learn how to visualize and interpret query plans using EXPLAIN and ANALYZE commands, gaining insights into execution time, data access methods, and potential bottlenecks. We’ll demonstrate how to identify common performance issues like missing indexes, inefficient joins, or suboptimal query structures by deciphering the information within a query plan.
Finally, we’ll connect the dots between PostgreSQL’s optimization techniques and the resulting query plans. By understanding how the planner weighs factors like data distribution, table statistics, and available resources, attendees will be empowered to write better queries and proactively optimize their database schema for maximum performance. This session is essential for developers and database administrators seeking to unlock the full potential of PostgreSQL and ensure their applications run smoothly and efficiently.
This talk provides an introductory overview of Artificial Intelligence (AI) and Machine Learning (ML), exploring key concepts and their application in building intelligent systems. It will highlight the essential AI/ML techniques, such as supervised and unsupervised learning, and discuss practical use cases in modern industries. The session also focuses on how PostgreSQL, with its powerful extensions like PostgresML, TimescaleDB, and PostGIS, supports the development of AI-powered applications. By leveraging PostgreSQL’s ability to handle complex datasets and integrate machine learning models, participants will learn how to build scalable, intelligent solutions directly within the database environment.
Success is a multiplier of Action, External Factors and Destiny.
Out of these three, the only controllable aspect is our action. Again, action is the result of our EQ, IQ, SQ, and WQ (Willingness Quotient) together.
We all want to be successful and keep trying to motivate ourselves with external factors. We read inspirational books, listen to great personalities, and whenever possible upgrade ourselves with more knowledge and the list goes on.
Indeed these are excellent motivators, but in this process, we forget the most important source of energy, YOU!
We read other stories to feel inspired, thinking “I am not enough!”
But, the day we start accepting ourselves, introspect, understand, and align our life purpose with our routine, we find the internal POWER. This is a continuous source of motivation and energy which we need at down moments. When we feel, lonely, stuck and seek help, our inner voice is the greatest companion.
But, how many times do we consciously think about our “Subconscious”?
“Journey to Self” is our structured coaching program where we take back focus from the outside and delve deep inside to find our inner strength. Focusing on self-acceptance and personal growth
I believe everyone has POWER within them!
Let’s be the POWERHOUSE!
Human, AI, and Personalized User Experience for DB Observability: A Composable Approach
Database users across various technical levels are frequently frustrated by the time-consuming and inefficient process of identifying the root causes of issues. This process often involves navigating multiple systems or dashboards, leading to delays in finding solutions and potential downstream impacts on operations.
The challenge is compounded by the varying levels of expertise among users. It is essential to strike the right balance between specialized and generalized experiences. Oversimplification can result in the loss of critical information, while an overwhelming amount of data can alienate certain users.
Developers and designers are constantly navigating these trade-offs to deliver optimal user experiences. The integration of AI introduces an additional layer of complexity. While AI can provide personalized experiences within databases, it is crucial to maintain user trust and transparency in the process.
The concept of personalized composable observability offers a potential solution. By combining the strengths of human expertise, information balance, and AI-driven personalization, we can create intuitive and user-friendly experiences. This approach allows users to tailor their observability tools and workflows to their specific needs and preferences.
This keynote will explore how L&D had got transferred from pre AI to post AI era and its efficiency job security?