DBMS > Dolt vs. EsgynDB vs. Microsoft Azure SQL Database vs. RocksDB vs. Transwarp ArgoDB

System Properties Comparison Dolt vs. EsgynDB vs. Microsoft Azure SQL Database vs. RocksDB vs. Transwarp ArgoDB

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Search engine

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

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.07
Rank	#350	Overall
	#153	Relational DBMS

Website

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

www.esgyn.cn

azure.microsoft.com/en-us/products/azure-sql/database

rocksdb.org

www.transwarp.cn/en/product/argodb

Technical documentation

docs.dolthub.com

docs.microsoft.com/en-us/azure/azure-sql

github.com/facebook/rocksdb/wiki

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

DoltHub Inc

Esgyn

Microsoft

Facebook, Inc.

Transwarp

Initial release

2018

2015

2010

2013

Current release

V12

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

C++

Server operating systems

Linux
macOS
Windows

Linux

hosted

Linux

Data scheme

yes

schema-free

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
HTTP REST

ADO.NET
JDBC
ODBC

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

All languages supporting JDBC/ODBC/ADO.Net

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

currently in alpha release

Java Stored Procedures

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

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.

Multi-source replication between multi datacenters

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

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