DBMS > DolphinDB vs. EsgynDB vs. Microsoft Azure Table Storage vs. Oracle NoSQL

System Properties Comparison DolphinDB vs. EsgynDB vs. Microsoft Azure Table Storage vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

A Wide Column Store for rapid development using massive semi-structured datasets

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Time Series DBMS

Relational DBMS

Wide column store

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

www.dolphindb.com

www.esgyn.cn

azure.microsoft.com/en-us/services/storage/tables

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.dolphindb.cn/en/help200/index.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

DolphinDB, Inc

Esgyn

Microsoft

Oracle

Initial release

2018

2015

2012

2011

Current release

v2.00.4, January 2022

23.3, December 2023

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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++

C++, Java

Java

Server operating systems

Linux
Windows

Linux

hosted

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

SQL-like query language

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

All languages supporting JDBC/ODBC/ADO.Net

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

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

optimistic locking

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

Access rights for users and roles

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