Querify Labs

We help technology companies build innovative data management products
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What we do

We create query engines, distributed protocols, and data management systems for large-scale data processing.

Distributed Protocols

Query Engines

Building a query engine is a challenging task, requiring careful design of executor, scheduler, memory manager, and other key components. We created multiple distributed query engines for both transactional and analytical workloads using modern approaches, such as vectorization and compiled execution.

We routinely use Apache Arrow for high-performance columnar processing.

Query Engines

SQL Optimizers

Query optimizer is one of the most important components of modern data management systems, having a critical impact on performance. We create powerful cost-based optimizers for distributed, federated and analytical engines.

We frequently use Apache Calcite as a back bone of our optimizers.

Data Engineering

Analytical Platforms

Data is at the heart of any modern business. Ability to analyze large volumes of data quickly is essential to stay ahead of your competitors.

We build custom analytical solutions using the modern open-source stack, including Apache Spark, Apache Flink, Apache Kafka, Trino, and open data formats Parquet, Orc, Avro managed by Apache Hive or Apache Iceberg.


Services - Design


Designing a new data management system is a challenging task. We create prototypes and do design reviews to ensure that you considered all trade-offs as early as possible.

Services - Research


Data processing is an active area of research. We bridge academic knowledge and practice to help you make better design decisions.

Services - Training


In-house expertise is essential for long-term product success. We conduct training to help your team accumulate solid knowledge of distributed systems and query processing.

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meet our team

Vladimir Ozerov



Vladimir founded Querify Labs with a vision to bridge the gap between cutting-edge research in data management and practical systems. Before that, Vladimir worked at Hazelcast, where he led the development of a distributed SQL engine for in-memory data. Vladimir loves to hack open-source products and talk about them at international IT conferences. Vladimir is a contributor to the Apache Calcite project.

Alexey Goncharuk



Alexey brings 10 years of experience building complex distributed systems and data storages. Before Querify Labs, Alexey worked at GridGain, where he was responsible for the overall product architecture, playing a pivotal role in developing persistence, replication, and transaction protocol for the Apache Ignite project. Alexey's area of interest includes query optimizers, concurrent algorithms, and formal methods. Alexey is a committer to the Apache Ignite project.

Roman Kondakov


Principal Architect

Roman is responsible for the architecture of data management systems at Querify Labs. Before joining the company, Roman worked at Yandex, the largest internet company in Eastern Europe, where he built the query optimization engine for massively parallel data processing. Roman is passionate about query optimization, looking for practical solutions to NP-hard problems on a daily basis. Roman is a contributor to the Apache Calcite and Apache Ignite projects.

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