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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. MySQL vs Symas LMDB

MySQL vs Symas LMDB

OverviewDecisionsComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
Symas LMDB
Symas LMDB
Stacks17
Followers36
Votes0

MySQL vs Symas LMDB: What are the differences?

Introduction:

MySQL and Symas LMDB are both popular database management systems, but they have some key differences that set them apart. In this article, we will explore these differences in detail.

  1. Storage Model and Speed: MySQL is a relational database system that follows the client-server model. It stores data in tables with predefined schemas and supports transactions and concurrent access. On the other hand, Symas LMDB is a lightweight embedded database library that uses a key-value storage model. It is designed for high-performance read-intensive applications and supports multi-threaded access. The key-value model of LMDB can provide faster access times compared to the structured tables in MySQL.

  2. Memory Management: MySQL requires a significant amount of memory to operate efficiently. It maintains a buffer pool to cache frequently accessed data, which can consume a substantial amount of memory. In contrast, LMDB uses a memory-mapped file for data storage, allowing the operating system to handle the memory management efficiently. This makes LMDB more memory-efficient compared to MySQL.

  3. Concurrency Control: MySQL offers various concurrency control mechanisms, such as locking and multi-version concurrency control (MVCC), to manage access to data by multiple users. It provides transaction isolation levels to maintain data integrity. LMDB, on the other hand, uses a reader-writer lock mechanism to handle multiple readers and a single writer. This allows multiple threads to read the database concurrently while ensuring data consistency. LMDB's lightweight concurrency control makes it suitable for highly concurrent environments.

  4. Data Durability: MySQL ensures data durability by writing transactions to a transaction log (redo log) and periodically flushing the changes to disk. This ensures that the committed transactions are not lost in case of a system failure. LMDB, being an embedded database, also provides durability by periodically syncing the data to disk. However, it does not support transaction logs or logging mechanisms like MySQL. This means that LMDB may have slightly higher data loss risk in case of a system failure.

  5. Scalability: MySQL is designed to handle large datasets and provides various scalability options, such as replication, sharding, and clustering. It can distribute data across multiple servers to achieve high availability and performance. On the other hand, LMDB is primarily designed for small to medium-sized datasets and excels in performance for single-threaded read-intensive workloads. While LMDB can handle concurrent access from multiple threads, its scalability options are limited compared to MySQL.

  6. Supported Data Types and Query Language: MySQL supports a wide range of data types, including strings, numbers, dates, and binary data. It also offers a comprehensive SQL query language for data manipulation and retrieval. LMDB, being a key-value store, supports only basic data types like strings and binary data. It does not provide a query language like SQL. Therefore, complex querying and data manipulation tasks are not as straightforward in LMDB compared to MySQL.

In summary, MySQL and Symas LMDB differ in their storage model, memory management, concurrency control, data durability, scalability, and supported data types and query language. MySQL is more suitable for relational database applications with complex querying needs, while LMDB excels in read-intensive workloads with high concurrency and limited scalability requirements.

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Advice on MySQL, Symas LMDB

Kyle
Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

DecidedonPostGISPostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k
Comments
Ido
Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k
Comments
Navraj
Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceonMySQLMySQLPostgreSQLPostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

401k views401k
Comments

Detailed Comparison

MySQL
MySQL
Symas LMDB
Symas LMDB

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

It is an extraordinarily fast, memory-efficient database which is developed for the OpenLDAP Project. With memory-mapped files, it has the read performance of a pure in-memory database while retaining the persistence of standard disk-based databases.

-
Ordered-map interface; Fully-transactional; Multi-thread and multi-process concurrency supported
Statistics
GitHub Stars
11.8K
GitHub Stars
-
GitHub Forks
4.1K
GitHub Forks
-
Stacks
129.6K
Stacks
17
Followers
108.6K
Followers
36
Votes
3.8K
Votes
0
Pros & Cons
Pros
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 490
    Open source
Cons
  • 16
    Owned by a company with their own agenda
  • 3
    Can't roll back schema changes
No community feedback yet
Integrations
No integrations available
Python
Python
Linux
Linux
Java
Java
Windows
Windows
macOS
macOS

What are some alternatives to MySQL, Symas LMDB?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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