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(Created page with " === What is memcp? === memcp is an open-source, high-performance, columnar in-memory database that can handle both OLAP and OLTP workloads. It provides an alternative to proprietary analytical databases and aims to bring the benefits of columnar storage to the open-source world. memcp is written in Golang and is designed to be portable and extensible, allowing developers to embed the database into their applications with ease. It is also designed with a focus on scalab...") |
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* Scalability: Designed to scale on a single node with huge NUMA memory | * Scalability: Designed to scale on a single node with huge NUMA memory | ||
* Adjustable persistency: Decide whether you want to persist a table or not or to just keep snapshots of a period of time | * Adjustable persistency: Decide whether you want to persist a table or not or to just keep snapshots of a period of time | ||
==== Further Reading: Scientific ==== | |||
* [https://www.vldb.org/pvldb/vol13/p2649-boncz.pdf VLDB Research Paper] | |||
* [https://cs.emis.de/LNI/Proceedings/Proceedings241/383.pdf LNI Proceedings Paper] | |||
* [https://wwwdb.inf.tu-dresden.de/wp-content/uploads/T_2014_Master_Patrick_Damme.pdf TU Dresden Research Paper] | |||
* [https://www.dcs.bbk.ac.uk/~dell/teaching/cc/paper/sigmod10/p135-malewicz.pdf Large Graph Algorithms] | |||
* https://wwwdb.inf.tu-dresden.de/research-projects/eris/ | |||
==== Further Reading: How MemCP was built ==== | |||
* [https://launix.de/launix/how-to-balance-a-database-between-olap-and-oltp-workflows/ Balancing OLAP and OLTP Workflows] | |||
* [https://launix.de/launix/designing-a-programming-language-for-distributed-systems-and-highly-parallel-algorithms/ Designing Programming Languages for Distributed Systems] | |||
* [https://launix.de/launix/on-designing-an-interface-for-columnar-in-memory-storage-in-golang/ Columnar Storage Interface in Golang] | |||
* [https://launix.de/launix/how-in-memory-compression-affects-performance/ Impact of In-Memory Compression on Performance] | |||
* [https://launix.de/launix/memory-efficient-indices-for-in-memory-storages/ Memory-Efficient Indices for In-Memory Storages] | |||
* [https://launix.de/launix/on-compressing-null-values-in-bit-compressed-integer-storages/ Compressing Null Values in Bit-Compressed Integer Storages] | |||
* [https://launix.de/launix/when-the-benchmark-is-too-slow-golang-http-server-performance/ Improving Golang HTTP Server Performance] | |||
* [https://launix.de/launix/how-to-benchmark-a-sql-database/ Benchmarking SQL Databases] | |||
* [https://launix.de/launix/writing-a-sql-parser-in-scheme/ Writing a SQL Parser in Scheme] | |||
* [https://launix.de/launix/accessing-memcp-via-scheme/ Accessing memcp via Scheme] | |||
* [https://launix.de/launix/memcp-first-sql-query-is-correctly-executed/ First SQL Query in memcp] | |||
* [https://launix.de/launix/sequence-compression-in-in-memory-database-yields-99-memory-savings-and-a-total-of-13/ Sequence Compression in In-Memory Database] | |||
* [https://launix.de/launix/storing-a-bit-smaller-than-in-one-bit/ Storing Data Smaller Than One Bit] | |||
* [https://www.youtube.com/watch?v=DWg4nx4KVLo memcp Announcement Video] | |||
Revision as of 17:24, 14 May 2024
What is memcp?
memcp is an open-source, high-performance, columnar in-memory database that can handle both OLAP and OLTP workloads. It provides an alternative to proprietary analytical databases and aims to bring the benefits of columnar storage to the open-source world.
memcp is written in Golang and is designed to be portable and extensible, allowing developers to embed the database into their applications with ease. It is also designed with a focus on scalability and performance, making it a suitable choice for distributed applications.
Features
- fast: MemCP is built with parallelization in mind. The parallelization pattern is made for minimal overhead.
- efficient: The average compression ratio is 1:5 (80% memory saving) compared to MySQL/MariaDB
- modern: MemCP is built for modern hardware with caches, NUMA memory, multicore CPUs, NVMe SSDs
- versatile: Use it in big mainframes to gain analytical performance, use it in embedded systems to conserve flash lifetime
- Columnar storage: Stores data column-wise instead of row-wise, which allows for better compression, faster query execution, and more efficient use of memory.
- In-memory database: Stores all data in memory, which allows for extremely fast query execution.
- Build fast REST APIs directly in the database (they are faster because there is no network connection / SQL layer in between)
- OLAP and OLTP support: Can handle both online analytical processing (OLAP) and online transaction processing (OLTP) workloads.
- Compression: Lots of compression formats are supported like bit-packing and dictionary encoding
- Scalability: Designed to scale on a single node with huge NUMA memory
- Adjustable persistency: Decide whether you want to persist a table or not or to just keep snapshots of a period of time
Further Reading: Scientific
- VLDB Research Paper
- LNI Proceedings Paper
- TU Dresden Research Paper
- Large Graph Algorithms
- https://wwwdb.inf.tu-dresden.de/research-projects/eris/
Further Reading: How MemCP was built
- Balancing OLAP and OLTP Workflows
- Designing Programming Languages for Distributed Systems
- Columnar Storage Interface in Golang
- Impact of In-Memory Compression on Performance
- Memory-Efficient Indices for In-Memory Storages
- Compressing Null Values in Bit-Compressed Integer Storages
- Improving Golang HTTP Server Performance
- Benchmarking SQL Databases
- Writing a SQL Parser in Scheme
- Accessing memcp via Scheme
- First SQL Query in memcp
- Sequence Compression in In-Memory Database
- Storing Data Smaller Than One Bit
- memcp Announcement Video