Publications

2026

1. ICDE

   RangeReduce: Query-Driven LSM Compactions

   Shubham Kaushik, Manos Athanassoulis, and Subhadeep Sarkar

   42nd IEEE International Conference on Data Engineering, May 2026

   Abs PDF Slides Talk

   Log-structured merge (LSM) trees are widely used in the storage layer of modern ingestion-optimized data stores. The high ingestion throughput, however, comes at the cost of sub-optimal range query (RQ) performance. This is because LSM-trees arrange the data as a hierarchical collection of sorted runs, which implies that every RQ must (i) probe all sorted runs to locate the qualifying entries, (ii) scan and merge the entries from all qualifying runs, (iii) filter out the logically invalidated entries by updates and deletes on the fly, and (iv) return the most recent version of each qualifying key. This leads to high read amplification and significant redundant work in terms of superfluous I/Os to storage and wasted CPU cycles, which is exacerbated in the presence of updates and deletes. Additionally, during compactions, the same data is read and written multiple times, further amplifying the read and write amplification. In this paper, we introduce RangeReduce, an RQ-optimized LSM-engine that uses RQs as a hint to compact data that is already read into memory as part of the query, and thereby, improves the overall performance of the storage engine.

2025

1. TPCTC

   Tectonic: Bridging Synthetic and Real-World Workloads for Key-Value Benchmarking

   Alexander H. Ott, Shubham Kaushik, Boao Chen, and 1 more author

   17th TPC Technology Conference on Performance Evaluation & Benchmarking, Sep 2025

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   Key-value stores are the backbone of many modern SQL- and NoSQL-based data systems, serving a variety of real-world applications. Despite their widespread adoption, existing key-value benchmarks fall short across multiple dimensions when accurately replicating complex and dynamic real-world workloads. In this paper, we introduce Tectonic, a Rust-based, highly configurable, and resource-efficient key-value workload generator designed to model the temporal, structural, and dynamic properties of real-world workloads. Tectonic offers fine-grained control over data access patterns, configurable composite key generation, dynamic workload generation, and generation of workloads with user-specified data sortedness — at 2x higher throughput and up to 84% lower memory footprint than the state-of-the-art.

2024

1. DBTest

   Anatomy of LSM Memory Buffer: Insights & Implications

   Shubham Kaushik, and Subhadeep Sarkar

   Proceedings of the Tenth International Workshop on Testing Database Systems, Jun 2024

   Abs HTML PDF Slides

   Log-structured merge (LSM) tree is an ingestion-optimized data structure that is widely used in modern NoSQL key-value stores. To support high throughput for writes, LSM-trees maintain an in-memory buffer that absorbs the incoming entries before writing them to slower secondary storage. We point out that the choice of the data structure and implementation of the memory buffer has a significant impact on the overall performance of LSM-based storage engines. In fact, even with the same implementation of the buffer, the performance of a storage engine can vary by up to several orders of magnitude if there is a shift in the input workload.

2019

1. JCSE

   Fault Modelling of an Object-Oriented System using CPN

   Shubham Kaushik, and  Ratneshwer

   International Journal of Computer Sciences and Engineering, May 2019

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   Object-oriented development is a mechanism in which objects provide services to other objects by various means like inheritance, polymorphism, etc. Faults, in object-oriented software, may occur at two levels i.e. object level and interaction level. In this paper, an attempt has been made to model several faults, in an object-oriented system, with the help of Colored Petri Nets.