DBMS > Dolt vs. LevelDB vs. ReductStore vs. RocksDB vs. SwayDB

System Properties Comparison Dolt vs. LevelDB vs. ReductStore vs. RocksDB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

A MySQL compatible DBMS with Git-like versioning of data and schema

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Document store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.85
Rank	#202	Overall
	#97	Relational DBMS

Score	2.26
Rank	#111	Overall
	#18	Key-value stores

Score	0.01
Rank	#379	Overall
	#39	Time Series DBMS

Score	2.96
Rank	#89	Overall
	#13	Key-value stores

Score	0.00
Rank	#385	Overall
	#60	Key-value stores

Website

github.com/dolthub/dolt
www.dolthub.com

github.com/google/leveldb

github.com/reductstore
www.reduct.store

rocksdb.org

swaydb.simer.au

Technical documentation

docs.dolthub.com

github.com/google/leveldb/blob/main/doc/index.md

www.reduct.store/docs

github.com/facebook/rocksdb/wiki

Developer

DoltHub Inc

Google

ReductStore LLC

Facebook, Inc.

Simer Plaha

Initial release

2018

2011

2023

2013

2018

Current release

1.23, February 2021

1.9, March 2024

9.4.0, June 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Business Source License 1.1

Open Source

BSD

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C++, Rust

C++

Scala

Server operating systems

Linux
macOS
Windows

Illumos
Linux
OS X
Windows

Docker
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
HTTP REST

HTTP API

C++ API
Java API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
JavaScript (Node.js)
Python
Rust

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

currently in alpha release

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

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