LeanStore is a high-performance OLTP storage engine optimized for many-core CPUs and NVMe SSDs. Our goal is to achieve performance comparable to in-memory systems when the data set fits into RAM, while being able to fully exploit the bandwidth of fast NVMe SSDs for large data sets. While LeanStore is currently a research prototype, we hope to make it usable in production in the future.
NVMe SSDs have become cheap (1 TB cost around 200 USD) and fast (achieving more than 2-7 GB/s bandwidth per device). Existing storage engines are not capable of exploiting such fast IO devices, in particular when multiple NVMe SSDs are combined in a single server. LeanStore has been designed from scratch for Directly-Attached NVMe Arrays to get the full performance from fast flash storage devices.
Using optimized index structures, LeanStore achieves very high in-memory performance and scalable synchronization techniques ensure that it scales very well on many-core CPUs. A lightweight buffer manager transparently keeps frequently-accessed data in RAM, while supporting arbitrarily-large data sets on SSD.
Similar to storage engines like RocksDB and WiredTiger, LeanStore can be embedded into applications by linking it as a library. It offers a C++ interface for basic data operations like point lookup, range lookup, insert, update, delete. Support for ACID transactions is currently under development. The source code is available under MIT license.
External Collaborators: Prof. Thomas Neumann, Prof. Alfons Kemper, Michael Haubenschild
Venue | Publication | Link |
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CIDR 2021 | Contention and Space Management for B-Trees Adnan Alhomssi, Viktor Leis |
pdf - code |
SIGMOD 2020 | Rethinking Logging, Checkpoints, and Recovery for High-Performance Storage Engines Michael Haubenschild, Caetano Sauer, Thomas Neumann, Viktor Leis |
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CIDR 2020 | Exploiting Directly-Attached NVMe Arrays in DBMS Gabriel Haas, Michael Haubenschild, Viktor Leis |
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IEEE Data Engineering Bulletin | Optimistic Lock Coupling: A Scalable and Efficient General-Purpose Synchronization Method Viktor Leis, Michael Haubenschild, Thomas Neumann |
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ICDE 2018 | LeanStore: In-Memory Data Management Beyond Main Memory Viktor Leis, Michael Haubenschild, Alfons Kemper, Thomas Neumann |
Date | Venue |
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April 2021 | HPI Research Symposium 2021 |
April 2021 | CMU Vaccination Database Seminar |
March 2021 | Dutch Seminar on Data Systems Design |
July 2020 | CWI Database Architectures Group |
January 2020 | TU Darmstadt |
January 2020 | CIDR |
November 2019 | University of Erlangen–Nuremberg |
November 2019 | University of Augsburg |
April 2018 | ICDE |
April 2018 | Imperial College London |
March 2018 | SAP HANA TechDays |
August 2017 | FGDB Symposium |
April 2017 | Columbia University |
April 2017 | Harvard University |
April 2017 | Massachusetts Institute of Technology |
March 2017 | Carnegie Mellon University |
Contact us (see Team for emails) if you are interested in a thesis, student job, or a Ph.D. position!