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What is memcp?

File:Https://www.memcp.org/images/0/03/Webapps with MemCP.svg

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

https://www.youtube.com/watch?v=g29FR4Jwius

Navigation

Introduction

• What is OLTP and OLAP
• History of the MemCP project
• Hardware Requirements
• Persistency and Performance Guarantees
• Current Status and Open Issues

Getting Started

• With Docker
• With Singularity
• Build from Source
• Contributing
• Introduction to Scheme

Frontends

SQL Frontend

• Supported SQL
• Advanced SQL Tutorial
• Replace MySQL with MemCP
• SQL over REST
• Supported Tooling
• How SQL Operators are implemented on MemCP

RDF Frontend

• Introduction to RDF
• Advanced Graph Querying
• RDF templating and model driven development

Custom Frontends

• In-Database WebApps and REST Services
• Websockets in MemCP

Administration

• Settings
• Process Hibernation
• Performance Measurement

Internals

How things work in MemCP

• Databases, Tables and Columns
• Shards, RecordIDs, Main Storage, Delta Storage
• Columnar Storage
• Transactions

Optimizations

• In-Memory Compression, Columnar Compression Techniques
• Temporary Columns
• Data Auto Sharding and Auto Indexing
• Parallel Computing

Further Reading

MemCP on Github

Scientific

• VLDB Research Paper
• LNI Proceedings Paper
• TU Dresden Research Paper
• Large Graph Algorithms
• https://wwwdb.inf.tu-dresden.de/research-projects/eris/

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