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  1. Stackups
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  5. RocksDB vs Symas LMDB

RocksDB vs Symas LMDB

OverviewComparisonAlternatives

Overview

Symas LMDB
Symas LMDB
Stacks17
Followers36
Votes0
RocksDB
RocksDB
Stacks141
Followers290
Votes11
GitHub Stars30.9K
Forks6.6K

RocksDB vs Symas LMDB: What are the differences?

Introduction

RocksDB and Symas LMDB are two popular database systems used for different purposes. While RocksDB is an embedded database for storing key-value data, Symas LMDB is a high-performance, memory-mapped key-value store. Despite their similarities as key-value databases, there are several key differences between the two. This article will outline and explain the six main differences between RocksDB and Symas LMDB.

1. Storage Type: RocksDB stores data on disk, making it suitable for applications with large data sets that cannot fit entirely in memory. In contrast, Symas LMDB stores data in memory-mapped files, providing fast and efficient access to data that fits into the available memory.

2. Write Amplification: RocksDB implements a log-structured merge-tree (LSM) data structure, which can cause write amplification. This means that writes can result in multiple disk operations, leading to increased disk activity and slower performance. On the other hand, Symas LMDB uses a B+ tree-like structure, which avoids write amplification, resulting in faster write performance.

3. Durability: RocksDB provides durability by writing data to disk at the cost of slower write performance. In contrast, Symas LMDB provides durability by syncing data to disk asynchronously, allowing for faster writes.

4. Concurrency Control: RocksDB uses a locking mechanism for concurrency control, which can lead to contention and decrease performance in highly concurrent workloads. On the other hand, Symas LMDB uses multi-version concurrency control (MVCC), which allows for better scalability and performance in concurrent environments.

5. Memory Usage: RocksDB utilizes more memory for its internal structures, such as memtable and block cache, leading to higher memory consumption. In contrast, Symas LMDB is designed to be memory-efficient and can operate with smaller memory footprints.

6. Development Language: RocksDB is primarily written in C++ and provides language bindings for various programming languages. Symas LMDB is written in C and provides language bindings for several programming languages, making it accessible to a wider range of developers.

In summary, RocksDB is a disk-based key-value store suitable for large data sets that cannot fit entirely in memory, while Symas LMDB is a memory-mapped key-value store with high-performance characteristics. RocksDB has write amplification, slower writes, and uses more memory, while Symas LMDB provides faster writes, lower memory usage, and utilizes a MVCC concurrency control mechanism.

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Detailed Comparison

Symas LMDB
Symas LMDB
RocksDB
RocksDB

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.

RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.

Ordered-map interface; Fully-transactional; Multi-thread and multi-process concurrency supported
Designed for application servers wanting to store up to a few terabytes of data on locally attached Flash drives or in RAM;Optimized for storing small to medium size key-values on fast storage -- flash devices or in-memory;Scales linearly with number of CPUs so that it works well on ARM processors
Statistics
GitHub Stars
-
GitHub Stars
30.9K
GitHub Forks
-
GitHub Forks
6.6K
Stacks
17
Stacks
141
Followers
36
Followers
290
Votes
0
Votes
11
Pros & Cons
No community feedback yet
Pros
  • 5
    Very fast
  • 3
    Made by Facebook
  • 2
    Consistent performance
  • 1
    Ability to add logic to the database layer where needed
Integrations
Python
Python
Linux
Linux
Java
Java
Windows
Windows
macOS
macOS
No integrations available

What are some alternatives to Symas LMDB, RocksDB?

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.

MySQL

MySQL

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.

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.

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